Remote PK / PD Module expert : Translational / Clinical Pharmacology Decision-Maker - AI Trainer ($175-$250 per hour)
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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 ...serp_jobs.internal_linking.show_moreserp_jobs.last_updated.last_updated_variable_days
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Remote PK / PD Module expert : Translational / Clinical Pharmacology Decision-Maker - AI Trainer ($175-$250 per hour)
MercorEast Orange, New Jersey, 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.