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

Posted on January 6th, 2021 by Thea Howe 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.  

ELSEVIER SOURCES AND METHODS

KEY BENEFITS

• 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