Translational Biology Expert

Role Overview

We are seeking PhD-level consultants with deep expertise spanning preclinical development through early clinical stages. The ideal candidate has led or meaningfully contributed to programs navigating the path from target validation through first-in-human studies, and can independently drive strategic decisions at key inflection points.

Consultants will support a range of high-impact deliverables – from preclinical study strategy and data interpretation through clinical program design and quantitative analysis.

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Key Areas of Expertise

We are looking for depth in one or more of the following areas. Candidates with breadth across multiple domains are especially valued.

1. Preclinical Study Design & Execution

• Designing and executing in vivo studies that link molecular mechanism to disease-relevant phenotypes

• Selecting appropriate preclinical systems (in vitro, ex vivo, animal models) with a clear rationale for human translatability

• Developing biomarker strategies that span target engagement through clinical response, including practical considerations around sample collection and assay performance

• Evaluating formulation and delivery approaches for tissue access across different modalities

• Troubleshooting inconclusive or negative preclinical results and recommending next steps

2. Preclinical Data Interpretation & Decision-Making

• Building exposure-activity relationships from in vivo datasets to inform clinical predictions

• Evaluating whether preclinical evidence supports drug activity at the intended site of action

• Updating mechanistic hypotheses as new data emerges and designing experiments to resolve ambiguity

• Assessing early safety observations and developing hypotheses for their biological basis

• Evaluating immunogenicity risk and its potential downstream consequences

• Supporting portfolio-level decisions (advance, pivot, terminate) grounded in data quality and residual uncertainty

3. Early Clinical Program Design

• Determining safe and pharmacologically relevant starting doses for human studies, including cross-species scaling and its limitations

• Designing dose escalation schemes informed by expected pharmacodynamic timecourses and safety margins

• Powering early-phase studies appropriately given biological variability and expected effect sizes

• Defining patient selection and enrichment strategies using available biomarker and epidemiological data

• Selecting endpoints – including when surrogate measures are sufficient vs. when clinical endpoints are required

• Planning interim analyses, safety monitoring, and adaptive decision rules

4. Quantitative Pharmacology & Clinical Modeling

• Exposure-response analysis and model-informed dose optimization

• Population PK and PK/PD modeling, including covariate identification and impact assessment

• Model-based support for dose escalation decisions using accumulating trial data

• Longitudinal efficacy modeling, including time-to-effect and trajectory-based analyses

• Sensitivity analyses addressing missing data, protocol deviations, and intercurrent events

5. Clinical Biostatistics

• Statistical analysis planning across endpoint types (binary, continuous, time-to-event)

• Multiplicity-adjusted hypothesis testing and sample size determination

• Subgroup and heterogeneous treatment effect analyses with appropriate false discovery controls

• Handling of estimand-related considerations, including missing data frameworks and dropout patterns

• Adaptive and interim monitoring design, including futility boundaries and alpha-spending functions

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Ideal Candidate Profile

• PhD, MD, and/or PharmD in pharmacology, pharmaceutical sciences, biostatistics, quantitative biology, or a related field (PharmD, MD also considered)

• 5+ years of industry experience in pharma, biotech, or CRO environments

• Based in the United States or United Kingdom

• Direct experience supporting at least one program from late preclinical stages through IND or into early clinical development

• Ability to independently evaluate complex data packages and deliver clear, actionable recommendations

• Strong communication skills for technical and non-technical audiences

Compensation

• Pay: $110 – $135/hour
• Type: Hourly contract
• Location: Remote