Global Head of DMPK & Translational PK

AiLux S.r.l.; Cambridge; Remote; GBP 150,000 - 190,000; Full time

Job summary

AiLux S.r.l. seeks an experienced Head of DMPK to establish and lead its Drug Metabolism and Pharmacokinetics capability, reporting to the VP, In Vivo Bioscience.

You will shape translational and quantitative pharmacology strategies across respiratory and immunology pipelines. Working at the interface of computational design, translational biology and preclinical development, you will embed DMPK considerations early and translate them into clear programme recommendations from hit identification

Qualifications

• PhD or equivalent in Pharmacokinetics, Pharmaceutical Sciences, Biology, Chemistry or related field.
• Significant industry DMPK/ADME leadership experience.
• Track record of enabling progression from discovery to clinical development.

Responsibilities

• Build and lead DMPK and translational pharmacology capability with strategic vision.
• Recruit and develop a multidisciplinary team spanning in vitro, in vivo, computational and translational DMPK.
• Provide data-driven, risk-balanced recommendations for candidate progression.
• Lead PK/PD, PBPK and translational modelling to inform first-in-human dose and study design.
• Integrate DMPK with AI-driven platform approaches across biologics and peptides.

Skills

Strategic leadership

People management

Cross-functional collaboration

Data-driven decisions

Education

PhD in Pharmacokinetics or related

Tools

PBPK modelling

Translational modelling

PK/PD modelling

Job description

AiLux S.r.l. seeks an experienced Head of DMPK to establish and lead its Drug Metabolism and Pharmacokinetics capability, reporting to the VP, In Vivo Bioscience.

You will shape translational and quantitative pharmacology strategies across respiratory and immunology pipelines. Working at the interface of computational design, translational biology and preclinical development, you will embed DMPK considerations early and translate them into clear programme recommendations from hit identification