GSK) Scientific Leader, Pre-clinical DMPK Drug Discovery Modeling

ViiV Healthcare is a global specialty HIV company, the only one that is 100% focused on researching and delivering new medicines for people living with, and at risk of, HIV. ViiV is highly mission-driven in our unrelenting commitment to being a trusted partner for all people living with and affected by HIV. Our aim is to think, act, and connect differently through a focus on education and treatment for HIV.

We go to extraordinary lengths to deliver the sorts of breakthroughs, both in treatments, care solutions and communities, that really count and take a holistic approach to HIV through developing and supporting sustainable community programs and improving access to care. We are fully committed to push through every challenge until HIV/AIDS is eradicated. ViiV has played a significant part in delivering breakthroughs that have turned HIV into a manageable health condition.

We offer the largest portfolio of HIV medicines available anywhere, and we continue our work to cater for the widest possible range of needs in response to the HIV epidemic.

We are aware of how much is at stake for those affected by HIV and we show up 100% committed to the patients every day. Our work culture is fast-paced, diverse, inclusive, competitive, and caring. But ViiV isn't just somewhere to work - it's a place to belong, an invitation to bring your very best, and a team full of impact-driven team members who are hungry to make a difference.

While we have been improving lives of HIV patients for 30 years, this is an especially exciting time to be at ViiV, as we evaluate novel approaches to treatment and prevention that could further reduce the impact of HIV on individuals and communities.

will serve in a matrix leadership role driving model-informed drug discovery across ViiV's Drug Discovery organization by developing and applying fit-for-purpose modeling and simulation approaches that enable rapid, data-driven decision-making for HIV drug discovery programs. This predominantly discovery-focused role partners closely with DMPK, Medicinal Chemistry, Biology, and Clinical Pharmacology to enable early dose predictions and to guide the design and selection of high-quality clinical candidates as rapidly as possible.

You will leverage your expertise in PBPK, IVIVE, PK/PD, formulation and route-of-administration modeling to develop modeling approaches and scalable tools that accelerate decision-making from target validation through candidate selection and into early clinical development for multiple modalities (e.g., small molecules, biologics, ADCs, LNPs, and PROTACs).

This role will provide YOU the opportunity to lead key activities to progress YOUR career. These responsibilities include some of the following:

• Develop and apply fit-for-purpose mechanistic and translational models (PBPK, IVIVE, PK/PD) to guide drug discovery teams toward the highest-quality clinical candidates

• Translate complex ADME, PK, PD, and translational data into actionable insights for project teams and senior leadership

• Apply modeling expertise across diverse modalities, formulations, and routes of administration, including long-acting therapies

• Build scalable computational tools, workflows, and prototypes that accelerate discovery decisions and candidate optimization

• Establish best practices, standards, and governance for modeling methodologies, tools, and computational workflows

• Contribute to scientific publications, regulatory submissions, and other technical documentation, and represent ViiV externally through regulatory interactions and scientific thought leadership

We are seeking professionals with the following required skills and qualifications to help us achieve our goals:

• Master's degree with 7 or more years of post-graduate experience, or a PhD with 4 or more years of post-graduate experience, supporting drug discovery programs from lead optimization to Phase I clinical studies

• Strong understanding of ADME principles and integration of standard DMPK workflows and data streams into empirical (e.g. NCA, compartmental modeling) and mechanistic modeling and simulation (e.g. PBPK, QSP) approaches to support rapid discovery decision-making

• Demonstrated ability to apply modeling and simulation approaches to influence key drug discovery decisions, including lead…