Translational Biology Expert

Weekday AI

9d•$110 - $135•Remote

About The Position

We are seeking PhD-level Translational Biology Experts with deep expertise spanning preclinical research through early clinical development. This role is ideal for professionals who have contributed to or led programs progressing from target validation to first-in-human studies, and can independently drive strategic decisions at critical development milestones. You will support high-impact initiatives including preclinical strategy, data interpretation, clinical program design, and quantitative analysis, helping guide data-driven decisions across the drug development lifecycle.

Requirements

PhD, MD, or PharmD in Pharmacology, Pharmaceutical Sciences, Biostatistics, Quantitative Biology, or related fields.
5+ years of industry experience in pharma, biotech, or CRO environments.
Direct experience supporting programs from late preclinical stages through IND or early clinical development.
Strong ability to independently evaluate complex datasets and provide clear, actionable recommendations.
Excellent communication skills for both technical and non-technical stakeholders.
Based in the United States or United Kingdom.
Candidates requiring H1-B or STEM OPT sponsorship are not eligible.

Responsibilities

Design and execute in vivo and in vitro studies linking molecular mechanisms to disease-relevant outcomes.
Select appropriate preclinical models with strong rationale for human translatability.
Develop biomarker strategies spanning target engagement to clinical response.
Evaluate formulation and delivery strategies for optimal tissue targeting.
Troubleshoot inconclusive or negative results and recommend next steps.
Build exposure-response relationships to inform clinical predictions.
Assess whether preclinical evidence supports target engagement and therapeutic activity.
Refine mechanistic hypotheses and design follow-up experiments.
Evaluate early safety signals and investigate biological drivers.
Assess immunogenicity risks and downstream implications.
Support portfolio decisions such as advancement, pivot, or termination based on data quality and risk.
Define safe and pharmacologically relevant starting doses for first-in-human studies.
Design dose escalation strategies informed by pharmacodynamics and safety margins.
Determine appropriate study power based on variability and expected outcomes.
Define patient selection and biomarker-driven enrichment strategies.
Select meaningful endpoints, balancing surrogate and clinical measures.
Plan interim analyses, safety monitoring, and adaptive trial designs.
Conduct exposure-response analysis and dose optimization.
Develop population PK/PD models and assess covariate impacts.
Support dose decisions using real-time trial data.
Perform longitudinal modeling of treatment response and efficacy trends.
Conduct sensitivity analyses addressing missing data and protocol deviations.
Design statistical analysis plans across varied endpoint types (binary, continuous, time-to-event).
Implement multiplicity adjustments and sample size calculations.
Conduct subgroup and heterogeneous treatment effect analyses.
Address estimand considerations, missing data, and dropout handling.
Design adaptive trials with interim monitoring, futility criteria, and alpha control.