PKPD Modelling Scientist

Exeltis; Madrid; Presencial; EUR 45.000 - 70.000; Jornada completa

Descripción de la vacante

A leading pharmaceutical company in Madrid is seeking a PKPD Modelling Scientist to shape drug discovery and development strategies. The successful candidate will apply innovative modelling approaches to generate quantitative insights, guiding decisions from preclinical research to clinical development. Responsibilities include developing PK/PD models and collaborating with cross-functional teams. The ideal candidate will hold a PhD related to pharmacometrics, fluent in English, and possess strong analytical skills. This role promotes diversity and equal opportunity in the workplace.

Formación

• Basic to initial professional experience in exposure-response modelling applied to drug discovery and/or development.
• Industry or academic experience in exposure-response modelling, including PK/PD, NLME, PBPK, and/or QSP.
• Demonstrated willingness to expand expertise in modelling and simulation methodologies.

Responsabilidades

• Develop and apply a range of modelling and simulation approaches for drug development.
• Generate quantitative insights and guide study design in preclinical and clinical settings.
• Drive preclinical‑to‑clinical translation combining various data sources.

Conocimientos

Fluent English

Strong leadership

Communication skills

Organisational skills

Educación

PhD in pharmacometrics, pharmacokinetics, pharmaceutical science, mathematics, or related field

Herramientas

Phoenix

R

NONMEM

PK-Sim

Descripción del empleo

Experience:

Basic to initial professional experience in exposure-response modelling applied to drug discovery and/or development.

PKPD Modelling Scientist Overview

As a PKPD Modelling Scientist, you will play a pivotal role in shaping drug discovery and development strategies through the application of innovative modelling and simulation approaches. This is a unique opportunity to contribute across all stages of drug discovery and development, from preclinical research and translational science through to clinical development. You will develop and apply a broad range of PK/PD models to generate quantitative insights that guide key project decisions, with a major focus on informing preclinical and clinical study design, dose selection, exposure-response characterization, and translational strategies to support progression into and through the clinic.

The role also offers the opportunity to apply advanced mathematical and translational modelling approaches to connect preclinical findings with clinical relevance and development plans. By integrating diverse datasets and performing simulations and quantitative analyses, you will help de-risk development, strengthen evidence-based decision‐making, and maximize the probability of clinical success. You will work closely with cross‑functional teams, transform complex data into clear and impactful recommendations, and communicate your findings to project teams, internal governance committees.

In addition, you will contribute to the development and implementation of innovative technologies, including AI‑driven approaches, to accelerate the drug development pipeline and support drug repurposing strategies.

Specific Responsibilities

• Develop and apply a range of modelling and simulation approaches—including PK/PD, NLME, PBPK, and/or QSP—to support decision‑making across preclinical, translational, and clinical drug development programmes.
• Generate quantitative insights by integrating diverse datasets and performing simulations to guide study design, dose selection and exposure‑response assessment in both preclinical and clinical settings.
• Drive preclinical‑to‑clinical translation by combining preclinical PK/PD, biomarker, and disease‑model data to predict human pharmacokinetics, pharmacodynamics, efficacious exposure ranges, and clinically relevant dosing strategies.
• Prepare and analyse datasets, interpret modelling outputs, and translate results into clear, scientifically grounded recommendations for project teams.
• Work closely with cross‑functional teams and communicate model‑based findings through presentations, technical documentation, and regulatory reports.

🕵️Requirements and personal skills

• Education: PhD in pharmacometrics, pharmacokinetics, pharmaceutical science, mathematics, or related field, with a focus on model‑based PK/PD approaches.
• Languages: Fluent English, knowledge of other languages will be an asset.
• Experience (years/area): Basic to initial professional experience in exposure‑response modelling applied to drug discovery and/or development.
• Specific Knowledge: Industry or academic experience in exposure‑response modelling, including PK/PD, NLME, PBPK, and/or QSP, with hands‑on expertise in scriptable modelling platforms such as Phoenix, R, NONMEM, or PK‑Sim. Understanding of pharmacokinetics, pharmacodynamics, and modelling and simulation principles. Ability to work with biological and clinical datasets and perform quantitative data analysis. Demonstrated willingness to continuously expand expertise in modelling and simulation methodologies, while exploring and applying emerging AI‑driven approaches. A strong record of scientific contribution and leadership, evidenced by relevant peer‑reviewed publications, is highly desirable.
• Personal skills: strong leadership, a high level of strategy and organisational and communication skills are essential.
• Initial contact through phone or email.
• 1‑2 interviews conducted virtually or in person.
• Continuous communication about the selection status.

COMMITMENT TO EQUAL OPPORTUNITY

INSUD PHARMA promotes gender equality and does not discriminate based on ethnicity, religion, sexual orientation, disability, or any other condition. We foster a diverse, inclusive, and respectful work environment.