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Global Medical Lead

  • Location: Berlin
  • £ Salary: Negotiable per year
  • Job Type:Permanent

Posted 15 days ago

  • Sector: Life Sciences
  • Contact: Peter Concannon
  • Expiry Date: 13 March 2024
  • Job Ref: JN -022024-483653

The Global Medical Lead will be responsible for driving the clinical development of individual pre-clinical/early clinical assets across various modalities and indications for Oncology. This person will provide clinical-scientific leadership ensuring a medically and clinically sound development strategy for one or more global development programs starting from pre-D1 up to Proof of Concept.

Responsibilities:

  • Guide the preclinical evaluation and validation of new oncology assets in line with the overarching Oncology strategy focusing on value, differentiation, and unmet medical need.
  • Act as the clinical leader and single clinical representative for the global program(s) assigned to them and represent them both, internally and externally.
  • Develop a clinical and medical development plan for the assigned assets with a focus on a definitive clinical experiment as well as an "end-to-end" mindset, which enables the collection of all relevant information for further seamless clinical development.
  • Be responsible for study medical/safety aspects and risk-benefit assessments supported by Pharmacovigilance and Clinical Trial Scientists.
  • Identify new opportunities for collaboration and manages relationships with new and existing internal and external partners within their assigned development program or internal/external workstreams.

Requirements:

  • Medical excellence: M.D., M.D./PhD or equivalent degree
  • 5+ years in direct patient care; board certification within Oncology/Haematology or associated subspecialties.
  • Solid experience in clinical drug development as an academic investigator or within a pharmaceutical/biotech environment.
  • Strong understanding of the scientific methods and tools used in early clinical development studies: biomarkers, translational modelling, and biostats.

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