Chat GPT Summaries Health Transparency & Pricing Fall 2023

Main blog at:

https://www.discoveriesinhealthpolicy.com/2023/12/xifin-offers-advanced-payor-analytics.html

See: Mittler, 2023, To be or note to be compliant?  Health Serv Res.

See: New leg in Congress, 12/2023.  https://www.theguardian.com/us-news/2023/dec/19/us-passes-healthcare-price-transparency-bill   HR 5378.  https://www.congress.gov/bill/118th-congress/house-bill/5378   At Becker's here.

Cf a JAMA article on how widely Part D generic prices vary. Hernandez 330:2390

Side bar [news summary by Chat GPT]

The document titled "Hospitals and Secretive Prices" provides a comprehensive overview of the hospital price transparency issue in the United States. The document includes several articles. Key points include:

1. Non-Compliance with Federal Rules: A significant portion of U.S. hospitals, including major chains and academic centers, have violated federal rules by not posting their care charges, as revealed by records obtained by Bloomberg News.

2. Government's Transparency Requirement: Since 2021, hospitals are mandated to be more transparent about their charges. However, nearly 20% of U.S. hospitals have been warned for rule violations.

3. Challenges in Implementation: Hospitals face challenges in making prices clear and available, and critics argue that CMS still has significant work to do in this regard.

4. Impact on Patients and Employers: The lack of price transparency makes it difficult for patients to shop for services and poses legal risks for employers in overseeing employee health plans.

5. Efforts for Better Compliance: CMS is working to enhance the effectiveness of price data and increase hospital compliance with the rules. Fines have been increased to encourage compliance, and some hospitals have been penalized.

6. Proposed Changes by CMS: Proposed changes aim to standardize data elements, improve enforcement, and align with other federal disclosure requirements.

7. Issues with Data Quality: Hospitals have been found to use varied file formats and lack standardization in reporting, making data hard to navigate and interpret.

8. Future Directions: CMS is committed to ensuring hospitals release data in useful formats for payers, policymakers, researchers, and patients.

The several articles are crucial for policymakers to understand the current state of hospital price transparency, the challenges faced in implementing it, and the ongoing efforts to improve compliance and data quality.

Chat GPT on Cancer Care Model v1 v2 at CMMI

 User

I understand that CMS ran an Oncology Care Model or OCM as one of the earlier experiments of CMMI, the Center for Innovation.  I understand the results were not much, but I'd be happy to hear if different.  Now there is some kind of second generation CMS OCM, what is it and what are the updates or differences?

ChatGPT

The original Oncology Care Model (OCM) launched by the Center for Medicare and Medicaid Innovation (CMMI) in 2016 aimed to improve care coordination and patient outcomes for cancer patients. However, the results of the OCM have been mixed. Financially, the model did achieve some savings, but these were offset by the costs of the program. A study by the Centers for Medicare & Medicaid Services’ OCM Evaluation Team found that the OCM led to a $499 relative savings in OCM versus comparison episodes. Despite these savings, the overall impact on the quality of oncology care was minimal, with only a small decrease in hospitalizations in the last month of life but no significant improvements in other quality measures, such as emergency department visits and patient-reported outcomes.

In response to the outcomes of the OCM, CMMI developed the Enhancing Oncology Model (EOM), which began on July 1, 2023. The EOM aims to address some of the shortcomings of the OCM. Key differences include a focus on high-risk patients, mandatory care management programs, expanded data reporting, and an explicit component on health equity. The EOM has a smaller patient cohort, targeting common tumor types, and requires participating practices to accept downside risk from the outset. It also places a greater emphasis on patient-centered care, with services tailored to the needs of individual patients.

However, the EOM also introduces new challenges. For instance, per beneficiary per month (PBPM) operating payments are significantly reduced compared to OCM, and the risk-sharing arrangements proposed by EOM are not true shared risks between provider and payer, as all the risk resides with the EOM participant. This structure exposes providers to potential financial penalties, which could be a deterrent, especially for smaller, independent practices with limited resources.

The transition from OCM to EOM reflects the ongoing efforts of CMS to evolve its approach to value-based care in oncology, with the aim of improving patient outcomes and reducing costs. However, the complexity of these models and the mixed results so far suggest that achieving these goals is challenging, and the success of the EOM remains to be seen​​​​​​​​.

Chat GPT Deciphers CMS Abbreviations and Care Models

 User

I see the Medicare agency using the abbreviation CHI, in the context of things like chronic illness and social determinants of health. How is it using CHI, I need to know the abbreviation.

ChatGPT

The abbreviation "CHI" in the context of Medicare and chronic illness is not explicitly listed in the common acronyms used by the Centers for Medicare & Medicaid Services (CMS). It's possible that CHI could refer to a specific program, initiative, or concept related to chronic illness within the Medicare system, but without a clear reference in the CMS's glossary or common acronym list, its exact meaning remains uncertain. It's advisable to refer directly to the specific context or document where you encountered "CHI" for a more accurate interpretation.

User

It turns out it’s community health integration, CHI, and as part of abroad effort to have better support for primary care, and especially the integration of basic care among patients with multiple needs such as for example, heart failure, plus cancer

ChatGPT

"Community Health Integration" (CHI) in the context of Medicare and chronic illness refers to efforts aimed at enhancing primary care support, particularly for patients with multiple health needs. This approach focuses on integrating basic care for individuals who may be dealing with complex health conditions, such as the coexistence of heart failure and cancer. The goal is to streamline and improve the overall healthcare experience for these patients by ensuring cohesive and comprehensive care management across different health issues.

User

The center for Medicare innovation had a special program in oncology for a number of years, called the oncology care model, the OCM …and quite a bit was written about this. One feature was that physician practices and oncology got an additional fee for the more global management of the patient, such as $100 per month, With the idea that this better global management would actually decrease total cost year by year. Here is my question. To the extent possible, what was the value of that extra monthly payment that went to physician practices who were participating in the oncology care model.

ChatGPT

Based on a quick search, here's what I found.

In the Oncology Care Model (OCM), physician practices received a Monthly Enhanced Oncology Services (MEOS) payment. This payment was set at $160 per beneficiary per month. The MEOS payments were designed to assist participating practices in managing and coordinating care for oncology patients during episodes of care. These payments were also included as part of the total episode expenditures and counted against each participant's total cost of care target.

The goal of these payments was to incentivize practices to provide comprehensive care and address complex needs of cancer patients undergoing chemotherapy, thus potentially reducing the overall cost of care while improving patient outcomes. The OCM was part of a broader effort by the Center for Medicare & Medicaid Innovation to improve effectiveness and efficiency in specialty care, including cancer care​​​​.

User

In Medicare what does the abbreviation AWV mean, I think it has something to do with dementia care. Or some kind of chronic care organization

ChatGPT

The abbreviation "WV" in the context of Medicare, especially related to dementia care, stands for "Annual Wellness Visit" (AWV). This visit is a part of Medicare's preventive care services, and it includes, among other assessments, the detection of cognitive impairment which could be crucial in the early diagnosis of dementia and Alzheimer's disease. The AWV is designed to create and update a personalized prevention plan for the beneficiary, helping to address and manage various health-related issues, including cognitive health​​.

User

In Medicare, what does the abbreviation TCM mean. I think it has something to do with the organization of chronic care.

ChatGPT

In Medicare, the abbreviation TCM stands for "Transitional Care Management." TCM services are designed to ensure effective coordination of care for Medicare patients as they transition from an acute care setting, like a hospital or inpatient facility, to a community setting. This transition period is critical, especially for patients dealing with a medical crisis, new diagnosis, or changes in medication therapy.

TCM services include a range of activities, such as contacting the beneficiary or caregiver within two business days following discharge, conducting a follow-up visit within 7 or 14 days of discharge (depending on the medical complexity), medication reconciliation and management, reviewing discharge information, and coordinating with community providers and services.

The two CPT codes used for billing TCM services are 99495 (for moderate medical complexity) and 99496 (for high medical complexity). These services can be furnished by physicians of any specialty, nurse practitioners, physician assistants, clinical nurse specialists, and certified nurse midwives, as long as they are legally authorized and qualified to provide TCM services in their state.

The primary goals of TCM are to reduce the likelihood of hospital readmissions, ensure continuity of care, and manage the overall health and well-being of patients during this vulnerable period. It's part of a broader shift in healthcare from volume-based to value-based care, emphasizing the importance of coordinated care and patient outcomes.

For more detailed information, you can refer to the American Academy of Family Physicians AAFP and Noridian Medicare.

User

Why can’t this simply be built as a E and M visit of similar complexity, and length? Giving it a separate number and calling it a separate thing, the TCM, seems just to complex it, when really not necessary.

ChatGPT

Transitional Care Management (TCM) services are distinct from regular Evaluation and Management (E&M) visits due to several key factors, and this distinction is why they are not simply billed as a regular E&M visit.

• Scope of Services: TCM involves more than just the face-to-face encounter. It includes comprehensive services that start from the day of discharge and continue for the next 29 days. These services entail managing and coordinating various aspects of a patient's care, including medical conditions, psychosocial needs, and daily living support.
• 
  
• Coordination and Complexity: TCM is specifically designed to address the complexities and coordination challenges that arise during the transition from an inpatient setting to community care. This period is critical and often involves higher risks of complications and readmissions. TCM ensures that various aspects of care, such as medication reconciliation, management of new or exacerbated health problems, coordination with community resources, and follow-up on pending tests and treatments, are adequately addressed.
• 
  
• Billing and Reimbursement Structure: TCM has a specific billing and reimbursement structure that recognizes the additional work and coordination efforts required post-discharge. By having separate billing codes, Medicare acknowledges the unique challenges and additional time and resources needed for effective transitional care, which are not typically part of a standard E&M visit.
• 
  
• Prevention of Readmissions: One of the main goals of TCM is to reduce hospital readmissions, which are both costly and potentially harmful to patients. The comprehensive nature of TCM services aims to ensure that patients' needs are fully met in the critical post-discharge period, reducing the likelihood of readmission due to unaddressed medical issues or poor coordination of care.
• 
  
• Specialized Training and Expertise: TCM services may require specialized training and expertise in managing transitions of care, which goes beyond the scope of a standard E&M visit. This specialized focus is essential in ensuring that all aspects of the patient's care are considered and managed effectively during the transition period.

While it might seem that having a separate category for TCM complicates billing, it actually provides a structured and comprehensive approach to manage the high-risk period following a patient's discharge from a hospital or similar facility. This distinction helps in ensuring that patients receive the necessary attention and care coordination, ultimately improving their health outcomes and reducing the risk of readmissions.

For more detailed insights into the rationale behind TCM services and their billing, you can refer to the resources provided by American Academy of Family Physicians and Noridian Medicare.

User

What are the Medicare payment values for the codes? 99495 and 99496

ChatGPT

 

As of January 2022, the Medicare reimbursement rates for the Transitional Care Management (TCM) codes were:

CPT code 99495: Provides a one-time reimbursement of $209.02. This code is used for TCM with moderate medical decision complexity, requiring a face-to-face visit within 14 days of discharge.

CPT code 99496: Offers a one-time reimbursement of $281.69. This code is used for TCM with high medical decision complexity, requiring a face-to-face visit within seven days of discharge.

Please note that these rates are subject to change and may vary based on the annual updates to the Medicare Physician Fee Schedule. For the most current rates, it's advisable to check with Medicare or the appropriate Medicare Administrative Contractor (MAC). ​

ChatGPT reviews FDA and SOLVD documents (Exec Summary; Meeting PPT).

 User

2022 FDA 1020 Autogenomic SOLVED Presentation 45p PPT.pdf

PDF

2022 FDA 1020 AvertD SOLVED COMPANY EXEC SUMM 79p.pdf

PDF

The SOLVD company has developed the AVERTD genetic test, and is presenting it to the FDA.  They use both a Powerpoint deck and a Memorandum document.  please read both, and summarize the company's main points.  Then, please list the ten key takeaways from the materials.

ChatGPT

The SOLVD company's presentation to the FDA regarding the AVERTD genetic test provides a comprehensive overview of the product, its design, clinical study results, and potential benefits and risks. Here are the key takeaways:

• Purpose of AVERTD: AVERTD is a genetic test developed to assess the risk of developing Opioid Use Disorder (OUD) based on genetic factors. This is aimed to aid healthcare providers in making informed decisions regarding prescribing opioids for acute pain.
• 
  
• Study Design and Population: The clinical study for AVERTD was designed to ensure that the study population represented the intended use population. This included participants with varying severity levels of OUD and a control group without OUD.
• 
  
• Test Performance: AVERTD demonstrated sensitivity and specificity in identifying individuals with a genetic predisposition to OUD. The performance was consistent across different subgroups, including those with varying severity of OUD and those with or without mental health comorbidities.
• 
  
• Self-Reported Data Validation: SOLVD took measures to validate self-reported data on opioid exposure, using medical records and a tiered system to corroborate participants' information.
• 
  
• Mental Health Comorbidities: The study showed no significant difference in the prevalence of mental health and non-opioid substance use disorder comorbidities between participants who developed OUD and those who did not, indicating a diverse study population.
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• Applicability of Results: The results were applicable across different types of study sites, including those specializing in OUD treatment and general practice sites, suggesting broad applicability of the test results.
• 
  
• Potential Risks and Mitigations: SOLVD identified potential risks associated with false positive and negative results and proposed mitigations, including guidelines for opioid prescribing and patient education.
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• Educational Materials: The company plans to develop educational materials for both physicians and patients, emphasizing that genetics is only one factor in OUD risk and should be used in conjunction with a complete clinical evaluation.
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• Regulatory Strategy: SOLVD proposes a classification regulation for AVERTD with a series of Special Controls to ensure the safety and effectiveness of the test. [510k de novo]
• 
  
• Benefits Over Risks: SOLVD concludes that the benefits of AVERTD, including providing valuable genetic risk information for OUD, outweigh the potential risks when used as part of a comprehensive patient assessment.
• 
  
• These points encapsulate the essence of the AVERTD genetic test as presented by SOLVD to the FDA, highlighting its potential role in managing opioid prescriptions and addressing the opioid crisis through a more personalized approach to patient care.

User

2022 FDA 1020 Autogenomic AvertD FDA_EXEC SUMM 51pp.pdf

PDF

2022 FDA 1020 AvertD Gussow 45p FDA_PPT.pdf

PDF

Switching gears a little.  The SOLVD company has developed the AVERTD genetic test.  The FDA AGENCY is now presenting their view.   They use both a Powerpoint deck and a Memorandum document.  please read both, and summarize the FDA AGENCY main points.  Then, please list the ten key takeaways from the materials.  Note the FDA's viewpoint may be more critical than the company's view of itself.

ChatGPT

The FDA's evaluation of the AVERTD genetic test developed by SOLVD Health presents a critical and detailed assessment of the test's design, clinical study, and overall implications. Here are the key takeaways from the FDA's presentation:

• Clinical Study Design: The FDA highlighted complexities in the clinical study design of AVERTD, including the enrichment strategy and the selection of enrollment sites, which could impact the generalizability of the study results to the intended use population.
• 
  
• Study Population and Enrollment: Concerns were raised about the inclusion and exclusion criteria, as well as the reliance on self-reported index exposure to prescription opioids. This could affect the accuracy of the study's representation of the intended use population.
• 
  
• Test Performance: While acknowledging the reported sensitivity and specificity of the AVERTD test, the FDA expressed uncertainty about its performance in the intended use population, given the study's limitations.
• 
  
• Device Design and Genetic Factors: The FDA noted that the 15 SNPs evaluated by AVERTD are associated not only with Opioid Use Disorder (OUD) but also with other mental health disorders and substance use disorders. This raises questions about the specificity of the test for OUD risk.
• 
  
• Impact of Comorbidities: The FDA stressed the need to understand whether AVERTD is detecting the risk of OUD specifically or in addition to other comorbidities, given the overlap of genetic factors.
• 
  
• Benefit-Risk Analysis: The FDA acknowledged that a test demonstrating benefits outweighing risks could have significant public health benefits. However, they highlighted challenges in making a definitive benefit-risk determination for AVERTD.
• 
  
• Potential for Misinterpretation: The FDA was concerned about the potential implications of false negative and false positive results, including emotional ramifications and stigma associated with genetic testing.
• 
  
• Clinical Use Considerations: The FDA emphasized the importance of considering how AVERTD would be used clinically, including its role in the broader context of assessing risk for developing OUD.
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• Labeling and Risk Mitigations: The FDA discussed the potential need for specific labeling and risk mitigations to minimize the risks associated with the use of AVERTD.
• 
  
• Advisory Committee Opinions: The FDA sought expert opinions from their advisory committee on various aspects, including the impact of study design and population, device design, and clinical performance on the interpretation of study results and applicability to the intended use population.

These points reflect the FDA's cautious and critical stance on the AVERTD genetic test, highlighting the complexities and uncertainties involved in assessing genetic tests for OUD risk. The FDA's perspective emphasizes the need for rigorous evaluation to ensure the reliability and clinical utility of such tests.

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You [the AI] have now had the chance to read and review all four documents, two from the company and two from the FDA.   In fact, after these presentations, the Advisory Committee voted 11-2 against approval.   What are  ten key reasons or rationales that most likely led to the negative viewpoint of the experts who listened to all this?   Please explain each rationale (don't just list a few words as a rationale like "weak data.")

Chat GPT4:

After reviewing the presentations from both SOLVD Health and the FDA regarding the AVERTD genetic test, and considering the subsequent 11-2 vote against approval by the Advisory Committee, it's possible to identify ten key rationales that likely influenced this decision. These rationales reflect concerns about the test's design, implementation, and potential clinical implications:

Complexities in Clinical Study Design: The FDA highlighted complexities in the study design of AVERTD, which could affect its applicability to a general population. This includes the strategy for selecting enrollment sites and the representation of the intended use population. A study design that doesn't robustly represent the target population can lead to doubts about the generalizability of the results.

Accuracy of Self-Reported Data: The reliance on self-reported data for opioid exposure was a significant concern. There's a risk of inaccuracies in self-reported data, which could lead to misclassification of participants and affect the validity of the study findings.

Specificity of Genetic Factors: The FDA noted that the genetic factors assessed by AVERTD are also linked with other mental health and substance use disorders. This raises questions about the specificity of the test in predicting OUD risk, as opposed to a broader predisposition to addictive behaviors.

Impact of False Positives/Negatives: The potential for false positive and negative results was a serious concern. False positives could lead to undue anxiety or stigma, while false negatives might give a false sense of security, potentially leading to inappropriate clinical decisions.

Clinical Utility and Implementation: Questions about how the test would be used in clinical practice were prominent. The committee might have been concerned about whether the test's results would genuinely aid clinical decision-making or whether they might lead to overreliance on genetic factors at the expense of other important clinical considerations.

Benefit-Risk Balance: The FDA and the committee had to consider whether the benefits of the test outweighed its risks. Given the complexities and potential for misinterpretation, it's possible that they concluded the risks were too high relative to the potential benefits.

Labeling and Educational Materials: Concerns about how the test would be presented to both clinicians and patients, and the adequacy of educational materials to prevent misinterpretation, could have influenced the decision. Effective communication is critical for such a test, and any shortcomings here can lead to misuse or misinterpretation.

Generalizability of Study Results: The generalizability of the study results to a broader population was questionable, especially considering the selection criteria and the study settings. This might have led the committee to doubt whether the test would perform as expected in the general population.

Regulatory and Ethical Considerations: The ethical implications of genetic testing for OUD, including concerns about privacy, consent, and potential discrimination, may have been a factor. The regulatory landscape for genetic tests is complex, and any uncertainties here can be a significant barrier to approval.

Overreliance on Genetic Factors: There might have been concerns about an overreliance on genetic factors in assessing OUD risk. OUD is a multifactorial condition, and focusing too heavily on genetics might oversimplify its etiology and overlook other critical factors like environmental influences, personal history, and comorbid conditions.

These rationales reflect a combination of scientific, clinical, ethical, and regulatory concerns that likely contributed to the committee's decision against recommending approval of the AVERTD genetic test. They underscore the challenges in developing and evaluating genetic tests for complex conditions like OUD.

How I Got an AI Picture for my AvertD News Blog

 See my blog about AvertD, an FDA-approved gene panel related to opioid risk.

Here's how the image came about.

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Image please.  I am a journalist writing an article about this FDA press release, and I'd like an appropriate interesting image to use as collateral.  Thank you. [INSERT FULL FDA PRESS RELEASE AS-IS HERE]

Here is the image illustrating the recent FDA approval of a test for identifying an elevated risk of opioid use disorder. This image depicts a medical professional administering a cheek swab test, with a poster of a DNA helix in the background, symbolizing the genetic nature of the test. This artwork aims to convey a sense of hope, innovation, and care in the medical field, highlighting the importance of this new test in addressing the opioid crisis.

Thanks, but I don't think it's really the style that fits.   Could you go back to square one and use the press release to come up with a different artistic concept for the task?

Certainly! Let's create a new artistic concept based on the FDA press release about the approval of the first test for identifying an elevated risk of opioid use disorder.

In this new concept, we can focus on the theme of prevention and awareness in the fight against opioid addiction. The image could depict a symbolic representation of the new genetic test. Imagine a scene with a pair of hands gently holding a transparent, glowing DNA helix, symbolizing the delicate and intricate nature of genetic testing. Above the hands, we could have a soft, ethereal light source, casting a warm glow over the DNA helix, representing hope and innovation.

In the background, there could be a subtle outline of a medical environment, such as a laboratory or a doctor's office, to set the context. The scene would be bathed in soft, calming colors to convey a sense of serenity and the positive impact of this medical advancement.

This image would aim to evoke a sense of hope and the crucial role of medical science in understanding and preventing opioid use disorder, resonating with the breakthrough nature of the FDA's approval.

Let me create this image for you.

Here is the newly created image, offering a symbolic representation of the new genetic test for opioid use disorder. This artwork is designed to evoke a sense of hope and the critical role of medical science in understanding and preventing this disorder.

Could we try one more that emphasizes the interaction between bottles of pills and perhaps a floating diagram of a chemical morphine molecule, and the other modalit which is the DNA double helix?    That is, we use pill bottles and a morphine molecule to represent the addiction problem (in a sterile non graphic way) while also bringing in the new topic of DNA and double helix.    But things like butterflies were just odd and distracting.

The newly created image offers a visual representation of the balance between opioid addiction and genetic testing, capturing the essence of your request. This illustration juxtaposes traditional opioid medication with the innovative approach of genetic testing in understanding and preventing addiction.

User

   Yes, that's just it.  Yes.

ChatGPT

   I'm glad to hear that the image meets your expectations and fits well with your article's theme. If you need any more assistance or further modifications, feel free to ask!

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Just for fun.   Styles of film noir, Rembrandt, Egypt.

Chat GPT and Claude review FDA 26 page summary of AvertD Genetic Panel (10/2022)

This is a Claude AI, and ChatGPT4, summary of the FDA's summary of the AvertD genetic panel adcomm at FDA 10/20/2022.  Document here.   My main blog here.

CLAUDE.AI

Here is a 5-sentence executive summary of the FDA workshop on the AvertD genetic test panel:

• The FDA convened a workshop with experts to review the AvertD genetic test panel, which aims to help assess risk of developing opioid use disorder (OUD). Experts reviewed the test's methodology, clinical study design, and performance data. 
• The panel voted 13-2 against approval, citing concerns about the clinical study population not matching the intended use population, categorical high/low risk results, potential for misuse, and lack of real-world implementation data. 
• The sponsor defended the test but was open to altering the labeling and risk categorization. Overall, the panel felt risks outweighed benefits and sought additional data and safeguards before considering approval.

10 Key Takeaways:

1. The AvertD test uses 15 genetic polymorphisms to assess OUD risk from prescription opioids for acute pain.
2. The test provides a categorical high or low OUD genetic risk result.
3. The clinical study design likely introduced significant bias by recruiting heavily from opioid treatment sites.
4. The study population was 92% white and had unclear comorbidity evaluations, raising concerns about generalizability.
5. The Panel was very concerned about potential harms from categorical high/low risk results leading to over-reliance, under-treatment, or stigma.
6. The Panel sought a more nuanced, continuous-scale risk output rather than binary high/low results.
7. There were uncertainties about whether the 15 SNPs appropriately and exclusively assess OUD genetic risk.
8. The Panel sought further safeguards against off-label use and clear limitations in labeling and education.
9. The vote was 13 no, 2 yes for approval, citing study biases, categorical results, and potential for misuse as main concerns.
10. The FDA and Panel emphasized that more data on real-world implementation is needed before approval should be considered.

ChatGPT 4

Same prompt: The FDA reviewed the use of this new genetic test panel to help manage opioid prescriptions and risks. They generate this 26 page workshop summary. Please provide an executive summary of the work shop, and then, please list 10 key takeaways from the meeting.

The 26-page FDA workshop summary details the review of a new genetic test panel, AvertD, by AutoGenomics for managing opioid prescriptions and risks. The workshop included presentations by the FDA, sponsor (SOLVD Health), and public opinions. Key discussion points revolved around AvertD's design, its use of 15 SNPs to assess genetic risk for Opioid Use Disorder (OUD), study design concerns, and its potential impact on clinical practices. The panel critically evaluated the test's effectiveness, data representation, and implications for patient care, considering both benefits and risks.

Key takeaways from the meeting include:

1. AvertD's Purpose: AvertD is designed to assess genetic risk for developing OUD, to aid in decision-making regarding opioid prescriptions.
2. Test Design: The test evaluates 15 SNPs associated with OUD, using a cheek swab sample processed in a CLIA-certified lab.
3. FDA Concerns: The FDA raised concerns about the study design, including subject recruitment and the representation of the study population.
4. Sensitivity and Specificity: AvertD reported 82.76% sensitivity and 79.23% specificity in the clinical study.
5. Study Population Representation: Doubts were raised about whether the study population adequately represents the intended use population.
6. Risk of OUD and Comorbidities: There were discussions on whether the test could distinguish between OUD risk and other comorbidities.
7. Public Opinion: Varied opinions were presented during the public hearing, emphasizing both potential benefits and risks.
8. Panel's Concerns: Panel members expressed concerns about the risk of under-prescribing opioids, potential stigma, and reliance on genetic testing.
9. Data Gaps and Further Studies: The need for further studies and more data, especially regarding different subpopulations, was highlighted.
10. Labeling and Usage Guidance: Suggestions were made to refine the labeling to avoid over-reliance on the test and to guide its appropriate use

Chat GPT and CLAUDE review my Monthly Headlines Report

This is a monthly report that I write for my clients who are mostly genomics companies.  I also send it as a "freebie" to about 50 other consultants and policy influencers.   What do you think of it?

ChatGPT

The "2023 QuinnLLC Genomics Headlines" report for November 2023 is a comprehensive and detailed document. It covers a range of topics relevant to genomics companies, including:

General Headlines: Discussions on FDA regulations, the impact of presidential administration changes, and critiques of FDA's risk-benefit evaluations.

COVID-19 Related News: Insights into new COVID testing platforms, contracts for COVID test manufacturing, and updates on long COVID research.

Financial Headlines: Information on stock repurchases, funding rounds, and partnerships in the genomics industry.

Medicare, Payors, Health Systems, and AI: Analysis of Medicare policies, AI's role in healthcare, and the intersection of health systems with precision medicine.

Regulatory Updates: Developments in FDA regulations, legal perspectives, and industry responses.

Other Precision Medicine Headlines: Diverse topics including AI predictions in health outcomes, discussions on healthcare affordability, and updates on health innovation investments.

The report is well-structured, with clear sections and bullet points that make it easy to navigate. It provides valuable insights and analyses, making it a useful resource for clients, consultants, and policy influencers in the genomics field.

User

That's all true, but you've just summarized the table of contents and a few remarks the report is well structured with bullet points.  Can you provide a somewhat more insightful analysis?

ChatGPT

To provide a more insightful analysis of your "2023 QuinnLLC Genomics Headlines" report for November 2023:

Depth of Research: The report showcases in-depth research, particularly in sections on COVID-19 and regulatory updates. The detailed analysis of new testing platforms and FDA regulations indicates a strong understanding of current trends and challenges in genomics.

Relevance to Audience: The financial headlines and Medicare updates are highly relevant to genomics companies, offering insights that could influence business strategies and policy decisions.

Comprehensiveness: Covering a wide range of topics from AI in healthcare to precision medicine, the report provides a holistic view of the genomics industry, which is beneficial for a diverse audience of clients and influencers.

Analytical Insight: The report goes beyond stating facts, offering critical analyses of how developments like changes in presidential administration or healthcare affordability could impact the genomics field.

Potential Improvements: Consider including more case studies or real-world examples to illustrate key points. Additionally, infographics or visual summaries could enhance the report's appeal and accessibility.

Overall, the report is informative and well-crafted, providing valuable insights for your target audience in the genomics sector.

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CLAUDE.AI

Based on the summary, it seems like a very comprehensive and informative monthly report covering a wide range of important topics in genomics, precision medicine, and health policy. Here are a few thoughts:

The report covers the latest news and developments across many relevant areas - COVID, regulation, business deals, Medicare policies, health systems, etc. This provides great value to readers by consolidating a lot of key updates in one place.

There is a clear structure with numbered sections categorizing the different topics, making it easy to navigate. The use of sub-headings also helps with scanability.

It includes nice touches like the "AI Corner" to demonstrate applications of AI, the "Dollarized News" section to call out key financial deals, and the creative section numbers like #31 for Medicare and #57 for digital pathology. This makes the content more engaging.

The thorough referencing, with links to original articles and sources, adds significant credibility. Readers can easily check the primary material if they want more detail.

The writing seems clear, concise, and neutral in tone, avoiding hype or advocacy. This makes it readable and trustworthy.

Overall, it's an impressive, professionally-written industry roundup. Your clients likely appreciate this high-quality monthly analysis. For consultants and policy experts, it would serve as a very useful scan of the latest developments in the field. Nice work!

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This CLAUDE review is pretty good, but I asked the "please amplify" question anyway, even though it doesn't fit as well as it did in the first example.

User

That's all true, but you've just summarized the table of contents and a few remarks the report is well structured with bullet points.  Can you provide a somewhat more insightful analysis?

##

You're right, my initial feedback was fairly surface-level in just highlighting the structure and organization. Let me try to provide a deeper, more insightful analysis:

Key Themes

Upon closer reading, a few interesting themes emerge around regulation, business evolution, and technology adoption:

Tension around FDA's proposed LDT regulations, with skepticism about the rationale and likelihood of finalization. This could significantly reshape the competitive landscape.

Intriguing shifts in the business environment, like bio-pharma sponsors playing a bigger role at AMP and outsourced services gaining traction. This points to new partnership models and revenue streams.

Steady advances in liquid biopsy, AI/ML, and multi-omics capabilities, though questions remain about clinical utility and integration into practice. These technologies hold major promise but adoption is still early.

Areas of Innovation

I'm particularly struck by the sections highlighting innovative approaches to improve patient care:

Novel rapid diagnostics efforts at Penn, MGH, and elsewhere to accelerate lung cancer detection through multi-disciplinary teams. This could be a game-changer.

Growth of virtual tumor boards and precision medicine clinics to democratize access and expertise. This helps address disparities.

Creative efforts to apply AI/ML in areas like interpretation of variants, sepsis detection, and CAR-T optimization. This provides a glimpse into the art of the possible.

Potential Gaps

A few topics seem notable by their absence:

• Very little on health equity and access issues regarding precision diagnostics - this could warrant more attention.
• Minimal discussion of payer restrictions and denials around genomic testing usage, which remains a challenge.
• Limited info on test TATs and impacts of supply chain issues, which have caused major delays.

Just some examples of additional perspectives that could enrich the analysis. But overall, the report covers an immense amount of valuable territory and provides an illuminating overview of trends in this dynamic space. Let me know if you have any other questions

AI Invents Journalist Who Reviews Quinn Book List

My annual book list

https://bqwebpage.blogspot.com/2023/12/best-books-and-films-of-2023.html

Chat GPT 4 weighs in, in the role of a journalist who reviews book lists.

Review: 

An Eclectic Journey Through 2023's Best Books and Films - 

Bruce Quinn's Annual List

By [Journalist Name, Publication Name]

In the realm of annual book and film recommendations, few curators offer as intriguing and varied a selection as Bruce Quinn. His 2023 list is no exception, showcasing an eclectic mix that dances across genres, mediums, and subjects, reflecting the diverse palate of a true connoisseur.

A Deep Dive into History and Politics

Quinn's list opens with a strong emphasis on history and politics, a nod to readers with a penchant for understanding the intricate tapestry of past events shaping our present. "Disorder" by Peter Swenson is a standout, offering a century-long journey through American healthcare politics through the lens of the American Medical Association. This choice is particularly timely, considering ongoing debates around healthcare in the U.S.

The Intersection of Science and Society

In "Alzheimer's Disease Research," Christian Behl marries the history of science with current biomedical research, revealing the often tumultuous path of scientific progress. This book, alongside "How Data Happened" by Chris Wiggins and Matthew Jones, marks Quinn's list as one deeply invested in the stories behind scientific and technological advancements.

Personal Narratives in Biography

Quinn's taste in biographies is as eclectic as it is profound. Werner Herzog's "Every Man For Himself, and God Against All" offers a mesmerizing journey through the life of one of cinema's most enigmatic figures. In contrast, Maria Bamford's "Sure, I'll Join Your Cult" provides a candid, humorous, yet poignant look at life's tumultuous journey.

Films and Podcasts: A Broad Spectrum

The film and podcast selections are as diverse as their book counterparts. "Lucky Hank" and the docuseries "Arnold" showcase a blend of humor, action, and biography, while the indie foreign films like "The Perfect Candidate" and "Past Lives" highlight Quinn's eye for global storytelling that resonates on a deeply human level.

An Honorable Mention with Impact

Mark Manson's "The Subtle Art of Not Giving a F--" receives an honorable mention, but its inclusion speaks volumes about Quinn's understanding of contemporary culture's pulse.

A Personal Touch

What sets Quinn's list apart is not just the selections but his personal engagement with the content. His YouTube channel, "Bruce Quinn Playground," offers a unique perspective into his approach to media and culture, providing an interactive dimension to his recommendations.

Conclusion

Bruce Quinn's 2023 list is more than a collection of recommendations; it's a curated journey through the year's most impactful books and films. It reflects a mind that seeks to understand the world in its myriad forms, from the historical to the personal, from the scientific to the artistic. For those looking to expand their horizons or just find their next great read or watch, Quinn's list is an indispensable guide.

https://tinyurl.com/BQBOOK2023

Due Diligence and Genomics. Books, Blogs, and AI.

Amazon offers several books on  biotech due diligence, and Google offers more articles and free resources.

Google

https://www.orrick.com/en/Insights/2022/11/IP-Due-Diligence-Considerations-for-Prospective-Investors-of-Emerging-Life-Sciences-Companies  (focus on IP DD)

2023, Pitfalls in Clinical Genetics (incluedes medico-legal)

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9979801/

Amazon Books

Building Backwards to Biotech [Wisner; and other books on biotech entrepreneurship and management]

Scientific Due Diligence [Martinsberg; and other similar] [have ebook]

Some aspects of due diligence (valuation) are handled as such in Glorikian, Commercializing Novel IVDs. (have book)

###

Due diligence takes added importance (for both sides) in a tight funding environment.   Fierce Biotech layoffs.   Fierce Biotech no IPOs.    One firm from $20 in 2019, to $50 in 2020/2021, to $1, while sales rose from $217M to over $500M, $516M; while operating expenses were relatively flat. (NVTA).  Another firm (WGS GeneDx) from $660 in late 2020 to $2.50 in early 2024.   (And, "Goldman Sachs see Golden Era of Biotech,here.)

Martinberg book - Page and a half of payers, part of which is use defining 'payer'

On everything else, an extensive handbook

Building backwards - TPPs.  TPP can lead into a Frueh CU Analysis and into a Quinn Policy Analysis.

Negotiating with patent clerk is similar (people skills) to negotiating with a payor medical director (people skills) but ALSO do not over estimate the value (finite) of people skills re claims and data.   

###

What about the genomics side of due diligence?   I didn't find much on Google and I asked Chat GPT.

See also as Google Doc

https://docs.google.com/document/d/10lh44Hyx8InUxrDzYGVBuB_xQWaItasIbCFovLyqTf4/edit?usp=sharing

###

Much is known about doing due diligence in biopharma in general.   What are important considerations for due diligence of startup or young (series B or near IPO) genomics companies?   

Many of these seem to get funded yet burn a lot of money or go out of business, suggesting that the criteria for good due diligence in a  healthy way are not so well udnerstood for genomics companies.  Thanks in advance for your thoughtful and structured advice.

ChatGPT

Due diligence for startup or young genomics companies, especially those in Series B funding or nearing an IPO, involves a multi-faceted approach. The genomics field is complex and rapidly evolving, making due diligence even more critical. Here's a structured approach to consider:

Technology and Innovation Assessment:

Scientific Foundation: Evaluate the scientific basis of the company’s technology. Is it grounded in sound, peer-reviewed research?

Intellectual Property: Check the strength and breadth of patents. Are there potential infringements or limitations?

Technological Edge: Assess how the company's technology compares to existing solutions. Does it offer a significant advantage in terms of accuracy, speed, cost, or scalability?

Market Analysis:

Market Need: Identify the market demand for the company’s genomics solutions. Are they addressing a significant, unmet clinical or research need?

Competitive Landscape: Understand the competition. Who else is offering similar genomic solutions, and what is their market share and growth strategy?

[One can also take this in the full-on MBA direction, e.g. via Porter's Five Forces]

Regulatory Pathways: Investigate the regulatory landscape. What are the hurdles for market approval, and how is the company planning to navigate them?

[There are also some real quirky aspects of reimbursement, e.g. bundling rules]

Financial Evaluation:

Burn Rate and Financial Runway: Look at the company’s current burn rate and how long their capital will last.

Revenue Model: Understand how the company plans to make money. Do they have a viable, scalable business model?

Historical Financial Performance: Review past financial statements for insights into management's fiscal responsibility and efficiency.

Team and Governance:

Management Team: Evaluate the experience and track record of the leadership team. Do they have relevant experience in genomics and business?

Advisory Board: Consider the composition and expertise of the scientific advisory board.

Corporate Governance: Assess the company’s governance structure. Is there a healthy balance between founders, investors, and independent members?

Clinical and Regulatory Compliance:

Clinical Trials and Data: Examine any existing clinical trial data for efficacy and safety.

Regulatory Compliance: Ensure that the company is compliant with all relevant regulatory bodies and that they have a clear path to compliance in their target markets.

Partnerships and Collaborations:

Existing Partnerships: Look at current partnerships with other companies, academic institutions, or research organizations.

Potential for Future Collaborations: Assess the potential for future strategic partnerships that can provide technology validation, market access, or additional funding.

Risk Assessment:

Technological Risks: Consider the risks associated with the technology failing to meet its promises.

Market Risks: Assess the risk of market acceptance and competition.

Regulatory Risks: Understand the potential regulatory hurdles and how they might impact the company.

Exit Strategy and ROI Potential:

Exit Options: Consider potential exit strategies, such as IPO, acquisition, or mergers.

Return on Investment: Estimate the potential return on investment, considering the risks and market potential.

Remember, each company is unique, and the due diligence process should be tailored accordingly. It's essential to combine quantitative analysis with qualitative insights to get a comprehensive understanding of the company's potential.

####################

User

I'm thinking of a genomics company that raised $100M in genomics in 2020, another $200M in 2021, and yet by 2023 it was worth only pennies on the dollar.  What are some of the most common mistakes made by investors that are distinctive to genomics ?

ChatGPT

Investing in genomics companies can be particularly challenging due to the unique aspects of this field. 

When a genomics company that has raised substantial funding ends up significantly underperforming, it often points to specific mistakes or oversights by investors. Here are some common mistakes that are distinctive to investing in genomics companies:

Overestimating the Addressable Market:

Investors sometimes overestimate the size of the market that a genomics company can realistically capture. While the potential applications of genomics are vast, actual market demand, especially in the short to medium term, may be much smaller.

Underestimating Regulatory Challenges:

The path to market for genomics-based products can be fraught with regulatory challenges. Investors might underestimate the time, resources, and complexity involved in navigating these regulatory processes, especially for clinical applications.

Failing to Adequately Assess Scientific Validity:

The science behind genomics is complex and rapidly evolving. Investors may not have the expertise to critically evaluate the scientific underpinnings of a company’s technology, leading to investments in companies whose technologies are not as advanced or unique as believed.

Ignoring Reimbursement Hurdles:

In healthcare, having a great product is not enough; it must also be reimbursable by insurance companies or other payers. Investors might overlook the challenges in establishing a viable reimbursement model for genomic tests or therapies.

Overlooking Execution and Operational Risks:

Even with strong science and a significant market, operational inefficiencies, poor management, or execution failures can derail a genomics company. Investors might focus too much on the technology and not enough on the company’s ability to execute its business plan.

Misjudging the Competitive Landscape:

Genomics is a highly competitive field with rapid technological advancements. Investors might not fully appreciate the competitive pressures, including the emergence of new technologies that can quickly make existing ones obsolete.

Neglecting the Importance of Data and Privacy Concerns:

Genomic data is sensitive and subject to various privacy laws and concerns. Underestimating the importance of data security and privacy can lead to legal and reputational risks.

Assuming Linear Progress in a Complex Field:

Scientific and technological advancements in genomics don’t always follow a linear trajectory. Investors might expect steady progress without considering the potential for setbacks or the need for significant pivots.

Focusing Solely on Technology and Ignoring Commercialization:

A common mistake is being too focused on the technology itself and not on how it will be commercialized. Understanding the path to market, including sales, marketing, and distribution, is crucial.

Not Planning for Sufficient Capital and Time Horizons:

Genomics companies often require significant capital and long time horizons to develop their products and reach profitability. Investors might underestimate the amount of funding and time needed for the company to mature.

To mitigate these risks, investors in genomics companies need to conduct thorough due diligence, often involving experts in genomics, regulatory affairs, market analysis, and business development. This comprehensive approach can help in making more informed investment decisions in this complex and rapidly evolving field.

###

User

Considering our discussion of due diligence above.   Give a set of guidelines or rules for calcualting NPV of a new biotech product (in this case, a new genomic test).   Then I will ask another question.   

ChatGPT

Calculating the Net Present Value (NPV) of a new biotech product, like a genomic test, involves estimating the present value of future cash flows generated by the product, and then subtracting the initial investment. This process is crucial in investment decision-making, as it helps in evaluating the profitability of the investment. Here's a set of guidelines to calculate the NPV of a new genomic test:

Forecast Revenue Streams:

Estimate the potential revenues from the genomic test over its expected lifecycle. Consider factors like market size, adoption rate, pricing strategy, and competition.

Account for potential changes in the market, such as new competitors or technological advancements that could affect pricing or market share.

Estimate Costs:

Include all costs associated with bringing the genomic test to market, such as research and development, manufacturing, marketing, distribution, and operational expenses.

Factor in ongoing costs, including maintenance, updates, customer support, and any other recurring expenses.

Determine the Product's Lifecycle:

Define the expected commercial lifespan of the genomic test. Biotech products often have a finite market life due to technological advancements and changing market demands.

Consider the Time Value of Money:

Apply an appropriate discount rate to reflect the time value of money. This rate should reflect the risk profile of the investment and the opportunity cost of capital.

Calculate Net Cash Flows for Each Period:

For each year of the product's lifecycle, calculate the net cash flow (revenue minus costs).

Include a terminal value if the product is expected to generate cash flows beyond the forecast period.

Discount Future Cash Flows:

Discount the net cash flows for each period back to their present value using the chosen discount rate.

The sum of these discounted cash flows represents the total present value of future cash flows.

Subtract Initial Investment:

Deduct the initial investment costs from the total present value of future cash flows to determine the NPV.

Sensitivity Analysis:

Perform sensitivity analysis to understand how changes in key assumptions (like market size, costs, or discount rate) impact the NPV. This helps assess the risk and potential variability in returns.

Consider Regulatory and Market Risks:

Biotech products face significant regulatory risks. Account for the possibility of delays or additional costs due to regulatory hurdles.

Understand market risks, such as changes in healthcare policies, which could impact the adoption and pricing of the test.

Scenario Analysis:

Conduct scenario analysis to evaluate the NPV under different circumstances (e.g., best-case, worst-case, and most-likely scenarios).

Remember, calculating the NPV of a biotech product involves significant assumptions and estimates. It's important to use realistic and well-informed figures and to regularly update the analysis as new information becomes available.

####

Are step 4 and step 6 the same discount rate?

ChatGPT

Yes, in steps 4 and 6 of calculating the Net Present Value (NPV) for a new genomic test or any other investment, the same discount rate is typically used. Here’s a detailed explanation of each step:

Step 4 - Determining the Discount Rate:

This step involves selecting an appropriate discount rate to apply to future cash flows. The discount rate is a crucial figure that reflects the risk profile of the investment and the opportunity cost of capital. It's essentially the rate of return that could be earned on an investment of similar risk in the best alternative investment option.

Step 6 - Discounting Future Cash Flows:

In this step, you use the discount rate determined in step 4 to calculate the present value of future cash flows. Each year’s (or period’s) cash flow is discounted back to its present value using this rate. This process adjusts for the time value of money, recognizing that money available in the future is worth less than the same amount available today due to its potential earning capacity.

The consistency in using the same discount rate across these steps is important for a couple of reasons:

Risk Consistency: It ensures that the risk profile of the investment is consistently applied throughout the analysis. The discount rate reflects the risk, and using different rates could imply a change in the risk assessment in different stages of the calculation.

Accuracy in Present Value Calculation: Using the same rate throughout maintains the accuracy of the NPV calculation. Changing the rate would distort the present value calculation, leading to potentially misleading conclusions.

It's important to carefully determine the appropriate discount rate, as it significantly influences the resulting NPV. The chosen rate should reflect the specific risks and uncertainties associated with the biotech project, including market risk, technological risk, regulatory risk, and the company’s own operational risk.

User

It seems one would have to be careful about undercounting but also over counting risk.   For example, you could have a discount rate of 15% because biotech (genomics) is risky.  But would it then be double counting to multiple cash flow per year by 50% because there is a 50% risk of scientific failure?    Do you see where I am going?

ChatGPT

Yes, I understand your concern. It's important to balance accurately reflecting the inherent risks of a biotech (genomics) venture without inadvertently double-counting those risks in the NPV calculation. Let's break this down:

Setting the Discount Rate:

The discount rate, in this case, 15% for a high-risk biotech project, is intended to encapsulate the overall risk profile of the investment. This includes market risks, scientific risks, regulatory risks, and other uncertainties. It reflects the investor's required rate of return given these risks.

Adjusting Cash Flows for Specific Risks:

Separately adjusting the expected cash flows for specific risks, such as a 50% reduction to account for the risk of scientific failure, might be seen as an attempt to directly quantify a particular risk.

However, doing both — setting a high discount rate to account for overall risk and then also significantly reducing the expected cash flows for a specific risk — can lead to the issue of double-counting the risk. Here’s why:

Discount Rate Already Reflects Risk: The elevated discount rate is used because the investment is risky, which inherently includes the probability of scientific failure. Therefore, the future cash flows are already being 'penalized' for the risk through a higher discount rate.

Risk-Specific Adjustments: If you also adjust the cash flows directly for specific risks, you're effectively accounting for the same risk twice: once in the discount rate and again in the cash flow adjustment.

To avoid double-counting:

Comprehensive Risk Assessment: Ensure that the discount rate you choose comprehensively reflects the overall risk profile of the investment. This should include all significant risks, including the likelihood of scientific failure.

Use of Probabilistic Models: Instead of directly reducing cash flows, consider using probabilistic models or scenario analysis to account for specific risks like scientific failure. This approach can give a range of NPVs under different scenarios, reflecting various outcomes (success, partial success, failure).

Consistency in Approach: Be consistent in how you apply risk assessments. If you're using a high discount rate to account for general risk, avoid further penalizing cash flows for specific risks unless those risks are not adequately captured in the discount rate.

Balancing the assessment of risk in NPV calculations is more of an art than an exact science, especially in fields like biotech where uncertainties are high. It requires a nuanced understanding of both the industry and the specific venture, alongside careful consideration of how different types of risks are accounted for in the financial analysis.

User

OK, here's a related question.  We've talked about due diligence earlier, and I've got a book on scientific due diligence (by Martinsberg, 2018).    Then, we've talked about calculating NPV and considering things like scenario analysis.    

It seems there is a lot of overlap between "due diligence report" (which must financially value a company or project for investors) and "NPV analysis" which tells the investors the NPV of the project and how much they should invest and the NPV analysis may include things like scenarios.

Talk about similarities and differneces between a due diligence report (which may include NPV?) and a NPV report (which, if thoughtful, will understand the overall viability of the business without which NPV is just hypothetical).

ChatGPT

You've touched upon a very insightful aspect of financial analysis in the context of investing, especially in sectors like biotech and genomics. The due diligence report and NPV (Net Present Value) analysis, while interrelated, serve distinct yet complementary purposes in the investment decision-making process. Let's explore their similarities and differences:

Similarities:

Financial Evaluation: Both due diligence reports and NPV analyses are fundamentally concerned with the financial viability of a project or company. They aim to inform investors about the potential returns and associated risks.

Risk Assessment: A key component of both is assessing the risks involved. In due diligence, this encompasses a broader evaluation of risks (scientific, market, regulatory, operational), while in NPV analysis, risks are often quantified in terms of the discount rate and scenario analysis.

Future Projections: Both reports involve making projections about the future. Due diligence might assess the future market potential and growth prospects, while NPV calculations project future cash flows.

Scenario Analysis: Both may include scenario analysis to understand how different future conditions could impact the investment. This helps in assessing the robustness of the investment under various circumstances.

Inform Investment Decisions: Ultimately, the goal of both reports is to inform investment decisions – whether to invest, how much to invest, and under what terms.

Differences:

Scope and Focus:

Due Diligence Report: This is a broader evaluation that covers all aspects of a business – financial, legal, operational, technological, market, and regulatory. It's about understanding the company or project in its entirety.

NPV Analysis: This is a more focused financial tool used to evaluate the profitability of a specific investment. It's primarily concerned with the cash flows, the timing of these cash flows, and the discount rate.

Depth of Financial Analysis:

Due Diligence Report: While it includes financial analysis, it's just one part of a larger picture. The financial analysis in due diligence may not be as in-depth as a standalone NPV analysis.

NPV Analysis: This is a detailed financial model focusing specifically on cash flows, discount rates, and the net value of the investment over time.

Incorporation of Non-Financial Factors:

Due Diligence Report: It includes non-financial factors such as team experience, technology viability, legal issues, and competitive landscape, which may indirectly influence financial projections.

NPV Analysis: Primarily focuses on quantifiable financial factors. Non-financial factors might influence the assumptions but are not the central focus.

Purpose and Use:

Due Diligence Report: Used to get a comprehensive understanding of the investment opportunity, identifying potential red flags and areas of concern. It's a critical tool for decision-making.

NPV Analysis: Used to determine the value of an investment purely from a financial perspective. It's a tool to assess whether the investment makes financial sense.

Integration in Investment Process:

Due Diligence Report: Often the first step in the investment process, providing a detailed overview and understanding of the potential investment.

NPV Analysis: Usually comes after initial due diligence, used for a deeper financial dive and to justify the investment quantitatively.

Conclusion:

While there's overlap in assessing the financial viability and risks, a due diligence report is broader, encompassing a comprehensive analysis of the business or project. In contrast, an NPV analysis is a more focused tool, specifically used for assessing the financial worth of an investment. A thorough investment analysis would ideally include both: due diligence for a holistic understanding and NPV for a focused financial valuation.

User

But let me query this again.  The due diligence report includes a regulatory analysis, which might project a 30% risk of FDA failure to approve.    The NPV report isn't accurate of the NPV unless it's included that 30% in its projected cash flows somewhere along the line.

ChatGPT

You're absolutely right in noting that a comprehensive due diligence report's findings, particularly regarding regulatory risks like a potential FDA approval failure, should be integrated into the NPV (Net Present Value) analysis to ensure its accuracy and relevance. Let's delve into how this integration typically works:

Integration of Regulatory Risk into NPV Analysis:

When the due diligence report identifies a specific risk, such as a 30% chance of failing to obtain FDA approval, this risk needs to be factored into the NPV analysis.

This can be done through adjusting the projected cash flows to reflect the probability of different outcomes. For instance, the expected revenue streams could be weighted to account for the 30% risk of non-approval. This means only considering 70% of the potential revenue in the NPV calculation to reflect the approval uncertainty.

Scenario Analysis:

Another method is to use scenario analysis within the NPV framework. Here, you could calculate separate NPVs for different scenarios: one where the FDA approves the test (full revenue projections) and one where it does not (significantly reduced or zero revenue).

The overall NPV would then be a weighted average of these scenarios, based on the probabilities assigned during due diligence (e.g., 70% weight to the approval scenario and 30% to the non-approval scenario).

Discount Rate Adjustments:

While adjusting cash flows is one approach, another method is to adjust the discount rate to reflect the risk. If there's a significant regulatory risk, the discount rate can be increased to account for this added uncertainty. However, this method is less direct than adjusting cash flows and can be less precise in quantifying specific risks like regulatory approval.

Sensitivity Analysis:

A sensitivity analysis can also be performed to show how changes in the approval probability affect the NPV. This helps in understanding the impact of regulatory risk on the investment's viability.

Consistent Risk Assessment:

It's important that the risk assessments in the due diligence report and the NPV analysis are consistent. If the due diligence identifies a 30% risk of FDA failure, this same figure should be used in the NPV analysis to ensure alignment and accuracy.

Communication of Assumptions:

Any NPV analysis should clearly communicate the assumptions made regarding risks, including how the findings of the due diligence report have been integrated. This transparency is crucial for stakeholders to understand the basis of the financial projections and the associated risks.

In summary, while a due diligence report and an NPV analysis have different scopes and focuses, the findings from the due diligence, especially regarding specific risks like regulatory approvals, must be appropriately reflected in the NPV analysis. This ensures that the NPV calculation provides a realistic and relevant financial valuation of the investment opportunity.

#####

I am working on a white paper on how NPV and/or due diligence in genomic tests involves novel concepts and risks that are not present for the "typical" biotech drug.   Here are some of my ideas.   

1.  There is a standard approach to ROI of biotech products (cash flows, discout rate, etc).

2.  New kinds of policies affect genomics.   CMS has a 14 day rule prohibiting separate payment for the genomic test within 14 days of inpatient biopsy.   CMS has different bundling or packaging rules for proteomic and genomic tests even in the outpatient setting.   

3.  Pricing is highly constrainted by rules or funnels.    Your new genomic test may be "crosswalked" to a lower price test on the whim (self-justified) of a CMS administrator.  Or the test price may be set administratively by the gapfill method which is essentially CMS ad hoc price setting with minimum chance to appeal.   HEOR studies are likely to play no ruule at all.

4.  Genomic innovator labs often develop a genomic test with tens of millions of investment dollars, yet CMS may attempt to price at marginal cost and disrespect even a penny of the R&D cost.  In contrast, CMS pays doctors and hospitals about 105% of drug prices, where the acquisition drug price may include voluminous proportions for profit and R&D.    

5.  Coverage may be much slower, for example, you submit a dossier for genomic test coverage and wait 1 year for it to appear as a proposed LCD and 1 more year for it to appear as a final LCD - two years or 24 months of no revenue and ongoing burn rate.

6.  Valuation and assessment of genomics may use obscure (debated and debatable) concepts like "clinical validity" and "clinical utility".  Yes, these often have definitions but usually they are simplistic and circular and subject to widely differing opinions.   

7.  Genomics are often studied in retrospective trials, which is considered weaker data.   On the other hand, if you have a test that shows a drug does not work or has awful side effects, then it is hardly fair or viable to test in a prospective trial.   

8.  One armed trial may use syntheticaly designed control group (e.g. patients known from hospital records or claims forms) rather than RCT controlled gruops.   This may make the index test (studied in a one arm group) look too good, or perhaps underperform, in comparison to the "synthetic" control group.  

9.  there is science risk due to overfitting of genomic multi gene tests to a retrospective cohort.    Overfitting means that a new group will not fit the  test algorithm nearly as well, due to overfitting to the first group.

10.  Capital for client investments may be hard.  For example, pathology services are currently falling in nominal dollar terms, and clinical laboratory services are falling also in real dollar terms due to fixed prices in a time of inflation.   This squeezes margins of providers (hospitals, labs), making it harder for them to invest new capital in innovations.    

Please discuss these 10 points in the setting of a new paper on the role of these special factors in the field of due diligence and NPV/ROI assessment, when the topic is genomics.  I will use some  examples where the valuation of public genomics companies fell rapidly, suggesting that the market at the top end was poorly valuing the genomic labs' real prospects.

ChatGPT

Your white paper on the unique challenges in due diligence and NPV/ROI assessment for genomic tests in biotech sounds both fascinating and important. The 10 points you've raised highlight specific nuances and complexities that are distinctive to genomics, setting it apart from typical biotech drug development. Let's discuss these points in the context of their impact on due diligence and NPV/ROI assessment:

Standard ROI Approach and Its Limitations in Genomics:

While the ROI of biotech products typically follows a standard approach (cash flow analysis, discount rates), genomic tests challenge this framework with unique regulatory, pricing, and market dynamics. Understanding these nuances is crucial in due diligence and NPV calculations.

Impact of Specific Policies on Genomics:

Policies like the CMS 14-day rule or different bundling rules for genomic tests create a unique regulatory landscape that affects revenue and market access. Due diligence must include a thorough policy analysis, and NPV calculations should account for these regulatory constraints.

Pricing Constraints and Their Financial Implications:

The potential for CMS to 'crosswalk' genomic test prices to lower-priced tests or use the gapfill method for price setting introduces significant pricing uncertainty. This uncertainty must be factored into revenue projections and risk assessments in NPV analyses.

Disparity in R&D Cost Recognition:

The potential for CMS to price genomic tests at marginal cost, ignoring R&D investment, versus the more favorable pricing for drugs, highlights a valuation challenge unique to genomics. This disparity should be a key consideration in financial modeling and risk assessment.

Delays in Coverage and Revenue Impacts:

The slow process for coverage approval (like the LCD process) can lead to significant delays in revenue generation. This aspect should be incorporated into cash flow projections, with extended timelines and delayed revenue streams.

Subjectivity in Clinical Validity and Utility Assessment:

The subjective and often debated nature of terms like 'clinical validity' and 'clinical utility' in genomics can impact market acceptance and coverage. Due diligence should critically assess these factors, and scenario analysis in NPV calculations can help manage this uncertainty.

Data Strength from Retrospective Trials:

The reliance on retrospective trials in genomics, seen as weaker evidence compared to prospective trials, can affect the perceived efficacy and market acceptance of genomic tests. This should be a part of the scientific and market viability assessment.

Challenges with Trial Design and Data Interpretation:

The use of one-arm trials and synthetically designed control groups can lead to skewed data interpretation. This aspect should be critically evaluated during due diligence for its potential impact on the test’s perceived effectiveness and market credibility.

Risk of Overfitting in Multi-Gene Tests:

The scientific risk of overfitting in genomic tests, where a test tailored to a specific cohort may not generalize well, introduces both scientific and market risks. This risk should be assessed during due diligence and factored into the risk profile in NPV analysis.

Challenges in Securing Capital:

The financial environment of falling revenues in pathology and clinical laboratory services, amidst inflationary pressures, affects the availability of capital for investment in genomic innovations. This economic context is crucial for understanding market dynamics and financial feasibility.

In your paper, when discussing these points, it would be beneficial to frame them not only as challenges but also as areas where due diligence and NPV/ROI assessments need to adapt and evolve. Highlighting case studies where the valuation of public genomics companies fell rapidly could illustrate the consequences of underestimating these unique factors. This approach will provide a comprehensive view of the distinctive landscape of genomics, underscoring the need for a nuanced and tailored approach in financial analysis and investment decision-making in this field.

User

In part I will frame it as reasons the investors need to employ me as a fine expert.

ChatGPT

That's a strategic approach. Positioning yourself as a vital expert in the complex field of genomics investment is a smart way to highlight your value to potential investors. Here are some key aspects you might emphasize in your role as an expert:

Deep Industry Knowledge:

Emphasize your understanding of the unique challenges and nuances of the genomics industry, including regulatory landscapes, scientific advancements, and market dynamics.

Expertise in Navigating Regulatory Hurdles:

Highlight your ability to navigate complex regulatory frameworks and policies that significantly impact genomics investments, such as CMS rules and FDA approval processes.

Advanced Financial Modeling Skills:

Stress your capability in creating sophisticated financial models that accurately reflect the unique risk profiles and revenue potential of genomic tests, including handling uncertainties and scenario analyses.

Risk Assessment and Mitigation Strategies:

Demonstrate your expertise in identifying and assessing various risks specific to genomics investments, from scientific and technological risks to market and regulatory risks, and how you can develop strategies to mitigate these.

Ability to Translate Scientific Data into Business Insights:

Showcase your skill in interpreting complex scientific data and translating it into actionable business insights, crucial for making informed investment decisions in genomics.

Up-to-date Knowledge on Industry Trends:

Investors will value your commitment to staying abreast of the latest trends and developments in genomics, which can rapidly impact investment viability.

Track Record of Accurate Valuations:

If applicable, present case studies or examples where your involvement led to accurate valuations or successful investment decisions in the field of genomics.

Communication and Advisory Skills:

Highlight your ability to effectively communicate complex concepts to stakeholders and provide strategic advice based on comprehensive due diligence and financial analysis.

Network and Collaborative Efforts:

Your connections within the industry, including collaborations with scientific experts, regulatory advisors, and market analysts, can be a significant asset to investors.

Customized Approach:

Emphasize your capability to tailor your approach to the specific needs and contexts of individual investments, rather than applying a one-size-fits-all methodology.

By focusing on these areas, you can effectively position yourself as an indispensable asset to investors, offering unique expertise that can significantly influence the success of their ventures in the rapidly evolving and highly specialized field of genomics.

User

We  presented and discussed 10 ways in which genomic due dligence or valuation requires special knowledge, awareness, and attention that is not relevant to more general valuation of a biotech drug investment.    Could you walk through them and state whether each one, 

(a) pertains mostly to Due Diligence, 

(b) pertains mostly to writing an NPV report, or 

(c) pertains about equally to both.

ChatGPT

Certainly! Let's categorize each of the 10 points you've presented based on whether they pertain mostly to Due Diligence, NPV report writing, or both:

Standard ROI Approach and Its Limitations in Genomics:

(c) Pertains about equally to both: Understanding the limitations of standard ROI approaches in the context of genomics is crucial for both due diligence (to assess overall investment soundness) and NPV analysis (to ensure financial models are appropriately adapted).

Impact of Specific Policies on Genomics:

(a) Pertains mostly to Due Diligence: Policy impacts require a comprehensive understanding of the regulatory landscape, which is a key aspect of due diligence.

Pricing Constraints and Their Financial Implications:

(c) Pertains about equally to both: Pricing constraints affect market potential and profitability, essential in both due diligence for overall market assessment and in NPV analysis for accurate revenue forecasting.

Disparity in R&D Cost Recognition:

(c) Pertains about equally to both: Recognizing how R&D costs are treated differently in genomics versus traditional biotech drugs is important for understanding the financial health and potential of the company (due diligence) and for accurate cash flow modeling (NPV analysis).

Delays in Coverage and Revenue Impacts:

(c) Pertains about equally to both: Delays in coverage directly impact revenue timelines and market entry, which are crucial factors in both due diligence (for market strategy assessment) and NPV calculations (for cash flow projections).

Subjectivity in Clinical Validity and Utility Assessment:

(a) Pertains mostly to Due Diligence: The subjectivity in these assessments speaks to the market acceptance and scientific credibility of the genomic tests, which are key due diligence considerations.

Data Strength from Retrospective Trials:

(a) Pertains mostly to Due Diligence: The nature and strength of the data, especially from retrospective trials, is primarily a scientific and clinical evaluation, making it more relevant to the due diligence process.

Challenges with Trial Design and Data Interpretation:

(a) Pertains mostly to Due Diligence: The assessment of trial design and its implications on data interpretation is a part of the scientific and clinical scrutiny typical in due diligence.

Risk of Overfitting in Multi-Gene Tests:

(a) Pertains mostly to Due Diligence: Overfitting is a scientific risk, and understanding its implications on the test's applicability and reliability is a matter of scientific due diligence.

Challenges in Securing Capital:

(b) Pertains mostly to writing an NPV report: The financial climate and its impact on capital availability is a key consideration in financial modeling, affecting assumptions in the NPV report.

In summary, while many of these factors are relevant to both due diligence and NPV report writing, their emphasis varies. Due diligence tends to focus more on the comprehensive understanding of the business, scientific, regulatory, and market landscape, whereas NPV analysis is more concerned with the financial implications and modeling of these factors.

User

Thank you for your fine help this afternoon.

ChatGPT

You're very welcome! I'm glad I could assist you. If you have any more questions in the future, whether it's about biotech, finance, or any other topic, feel free to reach out. Have a great day and good luck with your work on the white paper!

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Above, we categorized the TEN POINTs as to whether they were most relevance to due diligence generally, or specifically to valuation such as NPV and ROI.     Now, can you offer (if possible) a different order of presentation in the white paper, that might be more logical or easier to assimilate for the reader.   The reader is someone who writes (or requisitions) due diligence projects in biotech and in genomics industries.    Let me mention, you might see TWO ways to reorder the ten points, if so, feel free to share both of them and a rationale.  Thank  you.

ChatGPT

Reorganizing the ten points for your white paper to make it more logical and easier for readers, who are primarily involved in biotech and genomics due diligence, can indeed be beneficial. The goal is to present the information in a way that flows naturally and builds upon each concept effectively. I'll propose two possible structures:

Structure 1: From General to Specific

This structure begins with broader issues and gradually moves towards more specific, detailed aspects. It's designed to start with foundational understanding before delving into the intricacies of genomic tests.

1. Standard ROI Approach and Its Limitations in Genomics: Start with a general overview of ROI in biotech and introduce why genomics requires a different approach.
2. Impact of Specific Policies on Genomics: Discuss how specific policies affect genomics differently than general biotech.
3. Challenges in Securing Capital: Introduce the financial context in which genomics operates.
4. Pricing Constraints and Their Financial Implications: Delve into how pricing is uniquely constrained in genomics.
5. Disparity in R&D Cost Recognition: Discuss financial recognition issues specific to genomics, building on the financial themes.
6. Delays in Coverage and Revenue Impacts: Transition into operational challenges, starting with coverage delays.
7. Subjectivity in Clinical Validity and Utility Assessment: Shift focus to clinical and market acceptance challenges.
8. Data Strength from Retrospective Trials: Discuss the nature of data in genomics and its implications.
9. Challenges with Trial Design and Data Interpretation: Further delve into the specifics of trial design.
10. Risk of Overfitting in Multi-Gene Tests: Conclude with a specific scientific challenge unique to genomics.

Structure 2: From Macro to Micro View

This approach starts with the external environment and regulatory context before moving into company-specific issues and scientific considerations.

1. Impact of Specific Policies on Genomics: Begin with the regulatory landscape that shapes the genomics industry.
2. Challenges in Securing Capital: Discuss the broader financial climate affecting genomics.
3. Pricing Constraints and Their Financial Implications: Explain how external pricing policies impact genomics.
4. Disparity in R&D Cost Recognition: Address financial valuation issues from an industry perspective.
5. Standard ROI Approach and Its Limitations in Genomics: Introduce the broader concept of ROI and its adaptation in genomics.
6. Delays in Coverage and Revenue Impacts: Move into operational aspects specific to genomic companies.
7. Subjectivity in Clinical Validity and Utility Assessment: Transition into market and clinical acceptance issues.
8. Data Strength from Retrospective Trials: Start focusing on the specifics of data quality in genomics.
9. Challenges with Trial Design and Data Interpretation: Delve deeper into the challenges of trial design.
10. Risk of Overfitting in Multi-Gene Tests: End with a detailed look at a scientific risk specific to genomics.

Rationale

Both structures aim to guide the reader through a logical progression: the first one is more thematic, starting with broad financial and policy contexts before moving into operational and scientific specifics. The second one adopts a macro-to-micro approach, beginning with the external environment and narrowing down to individual company and scientific challenges.

The choice between these structures can depend on what you believe will resonate more with your audience: a thematic journey through the complexities of genomics or a layered approach from broader industry trends to specific scientific challenges. Both aim to provide a comprehensive understanding of the unique nuances in genomics due diligence and valuation.

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Please summarize the uploaded PDF in about 100 words, please.

ChatGPT

The document is a comprehensive discussion on due diligence and Net Present Value (NPV) estimation in the context of genomics. It outlines the challenges and unique aspects of assessing startup or young genomics companies, especially those in Series B funding or nearing IPO. The paper covers a multi-faceted approach to due diligence, encompassing technology and innovation assessment, market analysis, financial evaluation, team and governance assessment, clinical and regulatory compliance, partnerships and collaborations, risk assessment, and exit strategy. Additionally, it touches upon common mistakes investors make in genomics, emphasizing the importance of a tailored due diligence process. The paper also explores calculating the NPV of new biotech products, particularly genomic tests, and discusses the overlaps and differences between due diligence reports and NPV analysis.

User

If someone were writing a white paper on due diligence in biotech, specifically, what is "special" about due diligence in genomics investments, would this material likely be useful?

ChatGPT

Yes, the material in this document would likely be very useful for someone writing a white paper on due diligence in biotech, specifically genomics investments. It provides a detailed overview of the unique challenges and considerations in assessing genomics companies, covering areas such as technology assessment, market analysis, financial evaluation, and regulatory compliance. This comprehensive approach is particularly relevant to genomics due to its specialized nature and the rapid pace of innovation in the field.

User

I understand the author found it difficult to locate written consensus knowledge about what is special when it comes to assessing due diligence in genomic test investments.

ChatGPT

The difficulty in locating consensus knowledge on due diligence for genomic test investments, as highlighted by the author, underscores the unique challenges in this field. Genomics is a rapidly evolving area with complex technology and regulatory landscapes. This lack of established consensus necessitates a more tailored and nuanced approach to due diligence, focusing on specific aspects like technological innovation, market potential, regulatory compliance, and clinical applicability. The document's in-depth analysis of these factors makes it a valuable resource for understanding the special considerations in genomic test investments.

User

It sounds like the field would find a white paper (from this material) useful and might circulate it widely, raising the visibility of the author.

ChatGPT

Indeed, a white paper based on this material could be highly useful in the genomics investment community. Given the complexity and specificity of due diligence in this sector, a well-researched and comprehensive document could serve as a valuable guide. Its circulation could not only fill a knowledge gap but also significantly raise the visibility of the author as a thought leader in this niche area, potentially influencing investment strategies and decision-making processes in genomic test investments.

User

What are some 'watch outs" or "cautions" the author should be aware of, as he crafts said white paper and circulates it through forums such as Linked In postings or webinars.  Alternatively, what special tips might maximize the value of the white paper that the author might not think of?

ChatGPT

When crafting and circulating a white paper on genomics investment due diligence, the author should consider the following cautions and tips:

Cautions:

1. Accuracy and Updates: Ensure the information is accurate and up-to-date, as genomics is a rapidly evolving field.
2. Confidentiality and Sensitivity: Be cautious about disclosing sensitive or confidential information, especially from proprietary sources.
3. Overgeneralization: Avoid generalizing findings across the diverse landscape of genomics investments.
4. Legal and Regulatory Compliance: Be aware of legal and ethical implications, especially regarding investment advice and claims.

Tips to Maximize Value:

1. Target Audience: Tailor the content to the knowledge level and interests of your target audience.
2. Case Studies: Include relevant case studies or examples to illustrate key points.
3. Collaboration: Consider collaborating with industry experts to add credibility and depth.
4. Interactive Elements: For webinars, include interactive elements like Q&A sessions.
5. SEO Optimization: For LinkedIn posts and other online content, use SEO strategies to improve visibility.
6. Follow-up Content: Plan for follow-up content or discussions to keep the audience engaged over time.