Frank S. David, MD, PhD
Managing Director, Pharmagellan
Professor of the Practice, Department of Biology, Tufts University
Student research opportunities (updated 2/28/25)
My academic interest is in how biopharma companies’ drug development strategies are influenced by policies and programs related to regulation, pricing, and other factors.[1]
As part of that effort, I have several opportunities available for students to contribute to ongoing or pending research projects. Some representative examples are below.
This work would be unpaid, but Tufts students may be eligible to receive independent study credit (e.g., via BIO 95 or BIO 195) after a trial period.
If you are interested in working on a project with me, please send the following materials to frank.david@tufts.edu:
Your CV or resume
A one-page cover letter describing your interest in the biopharma industry
An answer to one of the prompts below (pay attention to the word limits)
1. Drug approvals after failed clinical trials
Background: The U.S. Food and Drug Administration (FDA) requires new drugs to demonstrate “substantial evidence” of efficacy to obtain authorization for marketing.[2] However, there are several historical examples of drugs for which the efficacy data from clinical trials were mixed, as well as a handful of approvals without any bona fide clinical trial successes.
Prompt (answer both parts):
What is one reason why it might be appropriate for the FDA to approve a new drug that has failed one or more pivotal clinical trials? (up to 100 words)
Make the strongest argument you can against the case you made in (1). (up to 100 words)
2. Probability of success for clinical trials in various phases of development
Background: A key component of decision-making in drug development is estimating a project’s risk-adjusted net present value (rNPV).[3] The rNPV calculation uses an estimated probability of success (POS) for each phase of development. A prior study[4] derived new benchmark POS values for clinical phase transitions in biopharma and compared them to results from prior estimates. From this work, it is evident that the various estimates in the literature don’t agree completely with one another; for example, look at the “phase 2 to phase 3” row in Table 1 in the paper.
Prompt: What is one reason why studies to estimate the POS of clinical phase transitions for drug candidates might not agree with one another? (up to 150 words)
3. Impact of drug price legislation on biopharma innovation
Background: The Inflation Reduction Act (IRA) imposes mandatory price cuts on certain drugs made available under Medicare.[5] Opponents of the IRA argue the legislation will stifle biomedical innovation, in part by reducing investment in so-called “follow-on indications” pursued after the drug’s initial approval.[6] However, there are currently no data to establish a current benchmark of how approvals evolve over a drug’s lifetime that could serve as a baseline with which to compare pre- and post-IRA levels.
Prompt: Why might the IRA dissuade a company with an approved lung cancer drug from pursuing a follow-on approval for the drug in osteosarcoma, a rare bone tumor, even if there were a good scientific rationale to suggest the drug would also work in the latter indication? (up to 150 words)
[1] List of published articles: https://orcid.org/0000-0002-8025-4427
[2] https://www.fda.gov/media/133660/download
[3] For background, see https://www.pauljanssenfuturelab.eu/toolbox/rnpv-explained/
[4] See e.g., https://academic.oup.com/biostatistics/article/20/2/273/4817524 and citations therein
[5] https://www.cms.gov/inflation-reduction-act-and-medicare