COMPETENCES

28 years of experience in Life Sciences

Industry Focus: Life Sciences, MedTech, Medical IT, Pharma


Core competence and special expertise

  • Executive management, strategic planning, innovation and business development, portfolio management, marketing & sales, human resources and ad-hoc management
  • Hightech medicine, medical IT, contract development, QM/regulatory affairs, clinical studies for software, medical devices and drug development in indications such as oncology, cardiology, acute care, orthopedics, chronic wounds, urine incontinence


Industry experience

  • Patrik Scholler, PhD (Bio)Chemistry, has worked scientifically at the German Cancer Research Center and has been instrumental in building several startups as well as in strategic leadership and top management positions of international corporations, as CEO in life sciences companies and since 2016 as independent strategy consultant and ad-hoc executive (LinkedIn profile).


Partner

  • With over 20 renowned partner companies and established processes, all areas from regulatory affairs (Regenold), medical technology and IT contract development (several specialists in Germany and abroad), clinical validation and approval of digital therapeutics (dtXca) to patent applications (Eisenführ-Speiser) and recruitment (HealthCorp Partners) are covered in such a way that every challenge can be dealt with effectively.
  • When it comes to the use of AI in medtech products, Narges Ahmidi, PhD (see right, LinkedIn) provides support with her proven expertise.



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Narges Ahmidi
Narges Ahmidi
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Narges Ahmidi, PhD, a distinguished computer scientist, has authored over 50 scientific publications in AI-driven healthcare. Currently serving as SYNLAB International's global head of Medical AI, she earned her Ph.D. in AI in Medical Robotics from the Johns Hopkins University in the USA. Dr. Ahmidi founded and directed numerous research departments at esteemed institutions like Fraunhofer and Helmholtz in Germany. Her pioneering work focuses on causally-informed predictive models for healthcare, enabling the forecast of disease progression and the assessment of treatment efficacy through longitudinal Electronic Health Records analysis.


     

     
     
     
     
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