Richard Jaenisch

The deadline to comment on FDA's generative AI paper is Oct 19, 2026. We explain why professionals in pharma manufacturing should weigh in.

Jaenisch, Muraru, and Pandey join PharmTech's Cole to discuss FDA's generative AI paper, ARPA-H's SURPASS trials, and AI accountability.

Richard Jaenisch explains what FDA's real-world use case database means for CMC and quality teams navigating NAMs.

PharmTech AI Pulse Check panelists explain why attribution, audit trails, and sign-off matter more than AI watermark detection for GxP quality teams.

Richard Jaenisch examines whether FDA's NAM pathway truly shortens drug pipelines or just shifts the evidentiary burden elsewhere.

API-gated journals may skew pharma regulatory research as AI agents favor accessible sources, raising citation integrity and pharmacovigilance risks.

Richard Jaenisch explains why NAMs are compressing drug development faster than AI and what FDA's new nonclinical testing rule means for sponsors.

Shadow AI and vendor data retention put GMP records and trade secrets at risk. AI Pulse Check panelists outline what pharma AI policies require.

PharmTech AI Pulse Check episode 2 covers AI data governance, API-gated journals, watermarking limits, and why attribution beats detection in GxP.

Episode 1, Part 3 of PharmTech AI Pulse Check covers why INTerpath-001's AI isn't ChatGPT and names pharma manufacturing's biggest AI governance gaps.

Richard Jaenisch weighs how FDA's new NAM rule could reshape preclinical testing and what CMC teams should do now, on Manufacturing Intelligence.

Florin Muraru, Gourav Pandey, and Richard Jaenisch explain where human sign-off belongs as multi-agent AI and document-parsing models reach GxP.

Jaenisch, Muraru, and Pandey debate whether AI "slop" is infiltrating pharma SOPs and deviation reports and who should catch it first.

PharmTech AI Pulse Check debuts: pharma experts tackle GxP 'slop,' multi-agent validation risk, OCR document mining, personalized mRNA cancer therapy.

Richard Jaenisch, Open Biopharma breaks down AI's real limits in drug discovery, agent security risks, and what workforce readiness looks like by 2028.

In this episode, we discuss AI drug discovery hype, agent security risks, and why pharma's AI workforce bets remain unproven.

Richard Jaenisch surveys pharma's biggest recent AI deals with Chris Cole in part one of a two-part breakdown of the major moves.

In this episode of Drug Digest, experts from Sanofi, GxP Frame, and Open Biopharma explain how AI is transforming drug discovery, manufacturing, and workforce strategy and how strategic partnerships play a role.

CAI's Jon Thompson explains how digital twins cut cleanroom rework by up to 50% and pressure excursion investigation time by up to 70%.

CAI's Jon Thompson details how digital twins cut cleanroom commissioning time by up to 30% and accelerate GMP deviation investigations.

Mihaela Simianu and Austin Caudle join the show to discuss how digital container twins can improve pharma manufacturing, validation, and risk reduction.

In this episode of Manufacturing Intelligence, we break down digital twin use in pharma, from risk reduction and scale-up modeling to AI integration and virtual inspections.

In this clip from episode 1 of Manufacturing Intelligence, Richard Jaenisch of Open Biopharma discusses uses of AI for deviations and investigations in pharma.

In this clip from episode 1 of Manufacturing Intelligence, Richard Jaenisch of Open Biopharma discusses step 1 in adopting AI in pharma manufacturing.

Richard Jaenisch and Christopher Cole discuss AI in pharma manufacturing, covering learning steps, output evaluation, hallucinations, and FDA/EMA guiding principles.

Richard Jaenisch explains how digitally interactive SOPs and Human-AI Training Parallelization help build, measure, and continuously improve AI-era workforce skills.

In regard to their presentations at PDA Week 2026, Richard Jaenisch and David Jaenisch discuss balancing AI integration with human expertise, compliance, and IP protection.