SAN DIEGO--(BUSINESS WIRE)--Scientist.com, the premier R&D marketplace for the biopharmaceutical industry, announced today that it has partnered with leading contract research organizations (CROs), including Crown Bioscience, Imagen Therapeutics and Experimental Pharmacology & Oncology Berlin-Buch (EPO) to boost the number of disease models currently available on its Disease Model Finder (DMF) to over 8,000, making it one of the world’s largest, if not largest, database for proprietary cancer models. The DMF helps medical researchers in the field of oncology identify the most appropriate models for their preclinical drug development projects.
“With the relationship that Scientist.com has with many disease model suppliers, we can aggregate data across suppliers, enabling researchers to make quantitative comparisons between disease models very quickly and efficiently,” stated Javier Pineda, PhD, Data Scientist at Scientist.com. “In addition to rapid model comparisons across suppliers, the Disease Model Finder allows for automated purchasing through the Scientist.com marketplace, so that once a researcher finds the model they need, they can purchase the model or request services immediately.”
The Disease Model Finder uses several machine learning algorithms, such as clustering algorithms and dimensionality reduction algorithms, to process and aggregate the data from large, molecular, sequencing-based datasets from multiple suppliers. These algorithms also enable researchers to visualize high-dimensionality datasets in 2-D for direct, visual model comparisons, as well as conduct differential gene expression analysis for models of interest. In combination with the multifaceted filter functionality, this allows researchers to find and source appropriate models for their research much more efficiently.
“Scientist.com’s Disease Model Finder (DMF) allows researchers to accelerate their drug discovery projects by providing a centralized, curated dataset of models from leading CROs, including Crown Bioscience,” said Jeff Buchanan, Senior Director, Business Development at Crown Bioscience. “The DMF enables rapid model identification and decision making in a matter of minutes that previously would have taken weeks, and as a leader in preclinical drug discovery, Crown Bioscience is delighted to provide data for this valuable resource.”
Since its launch in the spring of 2021, the Disease Model Finder has added thousands of new disease models—including organoids, cell-derived xenografts (CDX), syngeneic models, immuno-oncology models and patient-derived cell lines—with more being added monthly.
“Adding Imagen’s patient-derived cell (PDC) model catalogue and our model characterization data to the Scientist.com Disease Model Finder will enable oncology drug developers to make more informed decisions about their programs,” said Jonathan Engler, Executive Chair and Acting CEO at Imagen Therapeutics. “Oncology drug attrition rates are still higher than other diseases and implementing PDCs – as advanced patient-derived preclinical models – at an earlier stage in drug development can significantly improve success rates, reduce costs, and ultimately lead to patient benefits.”
To begin browsing and purchasing oncology models, visit https://app.scientist.com/disease-model-finder
Scientist.com's mission is to empower and connect scientists worldwide. The company's digital research platform combines a custom-built, cloud native technology stack with white-glove customer and scientific support to enable scientists to run more innovative experiments in less time and at lower cost. Scientist.com leverages internally developed machine learning models to provide actionable insights that improve operational efficiency and effective research management. Scientist.com connects the world's top pharmaceutical companies, biotechnology companies and the US National Institutes of Health (NIH) to the world's largest network of scientific suppliers.
Visit scientist.com to learn more.
Join Scientist.com on social media: LinkedIn, Twitter, YouTube, Facebook and Instagram