Research and field analyses on the structural pressures reshaping life sciences regulatory — talent, complexity, AI adoption, and the gap between first-time filings and approval. Written by our regulatory team.
Why labor shortages hit small medical companies hardest.
Analysis of the 68% labor shortage impact and the disproportionate burden on SMBs in regulatory compliance — recertification, MDR transition, and the cost of being unable to compete for talent.
68% labor shortage · 50% wage premium at large firms · 17% still on paper-based systems
Regulatory talent shortages in U.S. life sciences.
A systemic-risk view of the regulatory affairs talent drought — retirement waves, hyper-expansion under MDR/IVDR, and the educational pipeline that hasn't kept pace.
60,000 biopharma jobs unfilled · 40% of senior RA leaders nearing retirement · only 552 MS regulatory science grads (2018)
Two decades of escalating complexity in FDA submissions.
A longitudinal analysis of FDA submission complexity (2005–2025). Submission length has grown 7× since 2005 as the agency shifted from document-centric to data-centric models.
7× longer submissions since 2005 · NDAs exceed 100,000 pages · 20,700+ CDRH submissions in 2024 · eCTD 4.0 transition underway
The declining efficiency of FDA initial filings.
Why first-cycle approval rates are falling even as eventual approval rates hold above 90%. The Refuse-to-File surge, the CRL trend, and the three categories of deficiency driving rejections.
CRL rates 5% → 21% (2015–2024) · ANDA first-cycle approval only 18.9% · 84.5% of RTFs cite scientific/technical gaps
When regulatory failure stalls global health.
The systemic impact of FDA approval failures on medical advancement. RTA gatekeeping, predicate drift, and the medical-device lag that ripples from U.S. submissions to international access.
75% of medical device startups fail before market · 1/3 of 510(k)s fail initial RTA · 20% of clearances rely on predicates >10 years old
Structural and regulatory barriers in MedTech.
Why medical devices remain a late AI adopter compared to finance and retail. The predicate problem, the validated-state paradox, and the clinical-evidence gap behind a 50% adoption lag.
Only 24% of medtechs use AI · 50% adoption lag vs other high-tech · 82% of devices via 510(k) · 25% of AI submissions had no clinical study