Technological advances facilitating research across preclinical disease models: report
Five technologies empowering preclinical disease modeling are providing preclinical research with highly accurate and precise services
SANTA CLARA, Calif. — Frost & Sullivan’s recent analysis, Technological Advances Facilitating Research across Preclinical Disease Models, finds that the cross-synergy among five disciplines—artificial intelligence-powered systems, gene editing, quantum computing, 3D bioprinting, and bioelectronics—is driving the adoption of preclinical disease models for a wide variety of therapeutic areas.
“Considerable business opportunities are emerging in the field of precision disease modeling worldwide; one of the main goals of the efforts relies on the support of collaborative research projects that firmly associate personalized medicine in human subjects with advances in cutting-edge technologies for preclinical research,” said Cecilia Van Cauwenberghe, TechVision industry principal at Frost & Sullivan, in a prepared statement. “Going forward, North America and the Asia-Pacific regions are heavily oriented to the use of gene editing and stem cell reprogramming, whereas the adoption of organ-on-chip microfluidic systems and biomimetic sensors have found greater adoption in Europe.”
Van Cauwenberghe added: “Further, additional research and development is needed to better combine the major strengths of some technologies as well as to generate more reception for additional developments that may also empower these systems.”
According to Frost & Sullivan, innovation in technologies empowering preclinical disease modeling is presenting immense growth opportunities for market participants, including:
- Symbiotic partnerships will bring solid collaboration models that enable the provision of highly accurate services.
- Innovation investments in accelerating innovative capabilities will be well-leveraged in the future by considering the high impact of new technologies.
- Precision solutions are dramatically empowering preclinical research by providing life sciences research tools never imagined five years ago while allowing impressive savings in drug discovery.
- AI-powered preclinical technologies are increasing attention as engines for highly valuable analyses and predictions for best-suited selections.