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Elsevier to Work with Heel for Mechanism-based Drug Action Discovery

Posted on January 6th, 2021 by in Pharma R&D

Elsevier, the data analytics business specialized in science and health, and Heel, a pharmaceutical company specialized in developing and manufacturing medicines made from natural ingredients, have recently completed a series of research projects with a focus on improving exploratory preclinical studies.

“We at Heel are pioneers in the field of systems research and have a strong commitment to scientific excellence and the generation of evidence. Our aim is to find out how these medicines work in the body and to develop therapies which are tailored even more to patients’ medical needs,’’ said Dr. Kathrin Hemmer, a scientist at Heel. “We chose to partner with Elsevier because of its expertise in scientific information search. Assistance from the Professional Services group allowed us to get a single access to all the Elsevier’s R&D solutions advancing our exploratory research programs.”

“Research success requires connecting, combining and harmonizing data from different sources. We are helping researchers to select the best evidence-based strategy for mechanism-based drug action”, said Dr. Taisiya Bezhaeva, Professional Services Consultant at Elsevier.

“Together with Heel, we designed a series of projects to find preclinical models for drug action discovery, identify key biomarkers, and research platforms validated by the international research community. We focused on the broad range of disease areas, overall covering more than 10000 literature sources, as well as FDA and EMA drug approval documents. We also supported researchers by providing key opinion leaders (KOL) and potential academic and commercial partners helping Heel to direct and facilitate the course of their studies”, said Dr. Maria Shkrob, Senior Consultant in Professional Services at Elsevier.  



  • Connecting, combining and harmonizing data from different sources
  • Big-data & evidence-based approach to identify complex molecular mechanisms and biological networks for natural active compounds
  • Such approach combined with advanced text-mining technologies and statistics is a powerful, feasible and universal analytic method to select the best strategy for exploratory research to demonstrate pharmacodynamic actions, safety and efficacy
  • Support to strengthen scientific credibility and facilitate market positioning

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