Remote PK/PD Module expert: Translational / Clinical Pharmacology Decision-Maker - AI Trainer ($175-$250 per hour)Mercor • Bowie, Maryland, US

Remote PK / PD Module expert : Translational / Clinical Pharmacology Decision-Maker - AI Trainer ($175-$250 per hour)

Mercor • Bowie, Maryland, US

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The client is seeking an external expert who brings a

decision-maker’s mindset
— someone who has personally driven translational pharmacology choices under governance and uncertainty.

###

Who we’re looking for

Has owned FIH starting dose, SAD / MAD design, and Phase 2 dose selection for multiple assets. - Participated in governance or review boards, defending dose / exposure rationale in front of senior leadership or regulators. - Demonstrates ability to balance

nonclinical → clinical translation

: tox, PK, PD, potency, and MoA. - Can articulate the

real decision calculus

behind dose selection (safety, pharmacology, speed-to-proof). - Capable of turning narrative judgment into

explicit decision rules and rubrics

for AI training and evaluation. ###

Experience level

~10+ years in major biopharma or biotech (e.g., Lilly, Roche, AbbVie, Amgen, Novartis, GSK, Regeneron, Vertex, Incyte, Gilead) or in specialized translational pharmacology consulting. - Has

personally led

FIH dose and / or SAD / MAD escalation for ≥2–3 assets. - Proven governance experience : IND sign-off, dose justification memos, exposure–response presentations. - CV or track record includes statements like _“led clinical pharmacology strategy and FIH dose selection”_ or _“accountable for exposure–response in Phase 1 / 2.”_ - Avoid pure modeling profiles; the ideal expert has

decision accountability

, not just analytical skill. ###

Expectations

Write “golden” FIH dose rationales and escalation strategies for representative programs. - Encode the

decision heuristics and trade-offs

used by senior translational leaders into structured guidance and rubrics. - Surface

unwritten decision rules

— when and why experienced teams override model-based recommendations.

Inputs given :

Representative drug programs or data packets (GLP tox summaries, PK / PD tables, potency & MoA context). - Target prompts for translational decision-making (e.g., _“Recommend FIH dose and escalation strategy given these data”_).

Expected outputs :

Golden Decision Memos :

exemplar dose justification memos that reflect the level of reasoning and format expected from top-tier translational pharmacologists. -

Decision Rubrics :

scoring guides capturing acceptable vs. unsafe dose rationales, missed edge cases, or failure modes. -

Meta-Layer Commentary :

short narrative explaining unspoken heuristics — how senior teams weigh risk tolerance, potency data, or tox uncertainty.

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