TL;DR: Precision Medicine Investment Due Diligence
- Oncology phase I-to-approval success remains low; biomarkers improve design but do not remove attrition (Wong et al., 2019)
- Target validation quality links to pipeline outcomes (Cook et al., 2014)
- Personalized therapies face reimbursement and evidence hurdles beyond discovery (Goetz & Schork, 2018)
- Investors should verify biomarker claims against primary literature with PMIDs, not pitch decks alone
- Motif accelerates cited literature review for diligence on biomarker platforms and enrichment strategies
From the Motif team: Investors and founders both need traceable biomarker evidence. We extract PMID-linked associations from PubMed, PMC, and Europe PMC and cross-reference to curated databases. We do not provide investment advice or financial projections.
Precision medicine investment pitches often lead with market size slides. Diligence that holds up under scientific review starts elsewhere: whether the biomarker claim replicates in published trials, whether the context of use is defined, and whether validation evidence matches the intended diagnostic or therapeutic pairing (Goetz & Schork, 2018).1
What the Published Record Shows About Risk
Wong et al. (2019) estimated oncology likelihood of approval at 3.4% in a clinical-trial registry sample from 2000 to 2015.2 Biomarker-enriched designs can improve power and interpretability, but they do not guarantee approval.
Cook et al. (2014) analyzed factors linked to AstraZeneca pipeline outcomes and highlighted target validation quality, exposure at the site of action, and safety margins.3 For precision medicine companies, diligence should trace whether biomarker claims in decks appear in independent cohorts in PubMed.
Murciano-Goroff et al. (2023) summarize how precision oncology has expanded around tumor profiling and targeted therapies, with indication-specific evidence requirements.4 A marker that guides therapy in one cancer may be exploratory in another; investors should flag indication drift in materials.
Questions Investors Should Ask (and Answer from Literature)
- Is the biomarker predictive, prognostic, or diagnostic under FDA-NIH BEST definitions (FDA-NIH, 2016)?5
- Which pivotal trials support the therapy-biomarker pairing, and do PMIDs appear in the data room?
- Are there conflicting cohorts or null interaction tests in the same indication?
- Does the companion diagnostic or LDT have published analytical validation separate from clinical association?
- What fraction of the target population carries the biomarker in published prevalence studies?
Kumar et al. (2023) modeled value questions for biomarker-guided NSCLC treatment, showing that economics depend on alteration prevalence, test cost, and effect size.6 Financial models need those inputs from cited sources, not assumed uptake curves.
Reimbursement and Adoption Beyond the Data Room
Witteveen et al. (2022) reviewed financing and reimbursement models for personalized medicine across 153 publications. Most diagnostics still flow through traditional fee schedules; performance-based contracts appear mainly for gene therapies and selected companion tests.7 A scientifically sound biomarker platform can still stall if payer evidence requirements differ from what satisfied investors in the Series B deck.
Johnson et al. (2024) note that biomarker qualification and companion diagnostic pathways require fit-for-purpose validation tied to a stated context of use.8 Diligence should separate regulatory clearance narratives from coverage decisions and from clinical adoption in community settings where testing infrastructure may lag academic centers.
Literature Diligence Workflow in Motif
- Define the diligence question (target, biomarker, indication, comparator)
- Search PubMed, PMC, and Europe PMC with auditable boolean queries
- Extract associations with effect sizes, study design, and PMIDs
- Flag discovery-only evidence vs. independent validation cohorts
- Cross-reference genes, variants, and drugs to ClinVar, PharmGKB, ChEMBL, and related sources
- Export cited evidence memos for investment committee review
Failure modes in diligence:
- Relying on vendor white papers without primary publications
- Treating a prognostic marker deck slide as predictive enrichment evidence
- Ignoring negative trials that do not appear in the pitch
- Confusing literature association with regulatory qualification or approval
For the clinical science behind precision medicine, read our blog on personalized medicine biomarker analysis to learn more. For validation stages after literature review, read our blog on biomarker discovery and validation to learn more.
References
- Goetz, L.H., & Schork, N.J. (2018). Personalized medicine: motivation, challenges, and progress. Personalized Medicine, 15(5), 341-352. PMID: 29935653
- Wong, C.H., et al. (2019). Estimation of clinical trial success rates and related parameters. Biostatistics, 20(2), 273-286. PMID: 29394327
- Cook, D., et al. (2014). Lessons learned from the fate of AstraZeneca's drug pipeline. Nat Rev Drug Discov, 13(6), 419-431. PMID: 24833294
- Murciano-Goroff, Y.R., et al. (2023). Precision Oncology: 2023 in Review. Cancer Discovery, 13(12), 2525-2531. PMID: 38084089
- FDA-NIH Biomarker Working Group. (2016). BEST (Biomarkers, EndpointS, and other Tools) Resource. PMID: 27010052
- Kumar, V., et al. (2023). A global analysis of the value of precision medicine in oncology: NSCLC. Lung Cancer, 178, 178-186. PMID: 36891190
- Witteveen, L.C., et al. (2022). Financing and reimbursement models for personalised medicine. Appl Health Econ Health Policy, 20(4), 501-524. PMID: 35368231
- Johnson, K.R., et al. (2024). The FDA biomarker qualification program. Nat Rev Drug Discov, 23(4), 267-283. PMID: 38291248
