DIA 2023 was in Panalgo’s hometown of Boston last week and as usual, it did not disappoint. This year’s theme was ‘Illuminate’ – shining a light on many important topics such as diversity in clinical studies, artificial intelligence (AI), and personalized or precision medicine. Some newer concepts surfaced as well, including a provocative discussion of Mark Cuban’s Cost-Plus Drug Program (does it solve the pricing problem?) as well as therapeutic modalities for ALS and the emerging role of digital biomarkers in patient screening for ALS. The discourse on the judicious use and creation of real-world data (RWD) and real-world evidence (RWE) continues within the DIA community and is threaded through this year’s theme triad: innovation; diversity, equity, inclusion (DEI); and AI. In this blog, our team offers highlights and insights from the DIA Global Annual Meeting.
Autopilot or Copilot?
Generative AI such as ChatGP and BARD are here to stay. And despite top researchers and CEOs warning against the ‘risk of extinction’ with AI, a DIA panel predicted that soon, generative AI will become like your mobile phone: you won’t leave home without it. In the medical practice setting, generative AI could drastically reduce the administrative burden for healthcare practitioners (HCPs) so that they can spend more time with their patients and improve treatment access by, for example, automating the execution of a prior authorization form.
Acknowledging the excitement and terror that coexist with AI, one DIA panelist noted that AI augments rather than replaces human judgment and is a copilot rather than an autopilot. AI can lead researchers towards the answers to complex questions much faster than with traditional methods: for example, rapidly finding genetic mutations in rare diseases. Much of the anxiety around AI no doubt arises from a lack of understanding of what it is and how it is created, but panelists warned against confusing explicability with transparency. The latter is of the utmost importance because responsible use of AI means knowing what data were used to train the model, even more than knowing how the model works.
Diversity, Equity & Inclusion (DEI)
There were many sessions at DIA 2023 in which DEI was the primary topic and undoubtedly a subtopic in most if not all other sessions. One panelist noted that in her company, diverse hiring leads to more diverse research questions that inspire more diverse study designs, participation, data, and algorithms. One of the most fascinating topics in DEI is the expanding definition of diversity. For many years, it referred primarily to race/ethnicity and biological gender. However, there has been much discussion around expanding the definition to include gender identity, economic background, and other social determinants of health (SDoH).
In the session entitled, “Is Mark Cuban Really Solving the Drug Pricing Problem?”, the panel’s answer to the question was essentially: ‘not really’. Although panelists applauded Cuban’s efforts to bring transparency to drug pricing and to disrupt a highly complex pricing paradigm, the conclusion was that Cuban is only helping a very small subset of Americans with his Cost-Plus Drug Program. As the Inflation Reduction Act (IRA) takes effect, millions of Americans on Medicare will benefit from a yearly cap ($2,000 in 2025) on out-of-pocket prescription drug costs, but purchases made through a program like Cost-Plus won’t be credited towards that cap. The impact of the IRA (with certain provisions taking effect as early as September of this year) is expected to be significant; so much so that some manufacturers are questioning the constitutionality of the law.
With the growth of next-generation sequencing and the ability to capture massive amounts of biomarker data directly from the patient, even the most common diseases such as lung cancer, depression and diabetes will reveal very rare, personalized subtypes. The ultimate outcome is that a bespoke treatment plan can be created for every disease or condition subtype. There is a tremendous opportunity to look to RWD and AI to recognize these disease thumbprints and generate a draft treatment plan.
ALS, Alzheimer’s, and Biomarkers
Neurodegenerative diseases such as Amyotrophic Lateral Sclerosis (ALS) continue to elude treatment because of the highly effective blood–brain barrier that prevents drugs and biologics from reaching their targets. The Revised ALS Functional Rating Scale or ALSFRS-R, stratifies severity of ALS, including respiratory function. The score is used to establish baseline severity at diagnosis and to assess disease progression over time. However, the ALSFRS-R may not be sensitive to clinically meaningful changes in function for all people with ALS. One innovation discussed at DIA was the use of more sensitive and objective outcomes measures, biomarkers, and prognostic modeling in recent clinical trials. There are also ongoing efforts examining digital biomarkers that can be collected from smartphones or wearable devices to capture changes in real-world behavior and function.
The FDA has focused resources on accelerated cures for ALS and other conditions and continues to evaluate and approve treatments for Alzheimer’s. On June 9th, FDA’s independent advisors voted unanimously that Eisai’s and Biogen’s and drug Leqembi (lecanemab) demonstrated a clinical benefit to patients, likely paving the way for full FDA approval on July 6th.
New Uses for Old Products
Just a week before DIA 2023, the FDA announced that colchicine – a drug used in Ancient Egypt for inflammation and in the US to treat gout beginning in 1961 – was approved for use in cardiovascular disease. When combined with statins, the 0.5-mg, once-daily tablet—branded as Lodoco—reduces risk of stroke, coronary revascularization, myocardial infarction, and cardiovascular death by 31% compared to the placebo in patients with atherosclerotic disease or with multiple risk factors for cardiovascular disease. The Lodoco story is a brilliant example of repurposing an old drug for new use with a robust clinical trial. And because colchicine has been around for more than 60 years, it comes with a well-established safety profile, always an unknown with a new treatment.
RWD, Safety, and Technology
In sessions highlighting the use and acceptance of RWD for regulatory purposes, content was centered around three themes: reliability, transparency, and relevance. Agencies such as the FDA, EMA, and NICE are especially focused on the relevance of data, and how to maintain relevance when data are deidentified from the patient. There is also a push for increased use of RWD – in the EU, there is actually a requirement for post market studies. However, speakers acknowledged that although consistency is key for regulatory certainty, there are differences across diseases and one solution will not work for all regulatory reviews.
Additionally, several key themes emerged around RWD and technology. As the wealth of real-world data continues to grow, standards must be put in place and linkages must be created to demonstrate the holistic patient journey. On the technology side, we must consider how to use technology to assist with the challenges of RWD, for example, streamlining data transfers between workflows. Although synthetic data remains a controversial topic in the RWD / RWE sector, one session urged that it cannot be overlooked as a source of large-scale data. However, questions and concerns remain surrounding the quality of – and the methods for generating – synthetic data.
For more information on how Panalgo can support your team’s judicious selection of RWD and transparent generation of RWE, contact us today. Panalgo stands firm with the DIA Community in its commitment to responsible use of AI, continued support of DEI, and innovation in the prevention, diagnosis, and treatment of disease in every sector of our industry.