AI-powered Disease Model Finder helps researchers identify preclinical oncology models
Scientist.com, the pharmaceutical industry’s leading marketplace for life science research, announced today that it has partnered with Charles River, Certis Oncology and other leading oncology CROs to launch a Disease Model Finder that helps medical researchers use genetic, cellular and patient data to find the most appropriate research models for their preclinical development projects.
“Our proprietary model selection software uses multiple machine learning algorithms to help researchers sift through large amounts of data and identify in vitro and in vivo models for their research,” stated Javier Pineda, PhD, Data Scientist at Scientist.com. “Scientists can filter by gene mutation, gene expression, cancer type or patient information, and then purchase without delay once the right model is identified.”
The Disease Model Finder brings together a wealth of data that can help scientists choose the right preclinical disease models. DNA sequencing data from CRO partners is uploaded and analyzed so that researchers can easily search for models based on the presence (or absence) of a mutated gene or by the up or down regulation of gene expression. Marketplace customers can then filter their search results based on cancer type, subtype and characteristics or patient information.
“Scientist.com’s new Disease Model Finderwill enable pharma and biotech researchers to find and purchase the most appropriate Charles River models for their drug development programs,” said Melissa Schroeder, E-Commerce Manager at Charles River. “Having access to advanced data that better matches a patient-derived xenograft (PDX) model with a research program will enable optimal study design, ultimately saving time and money as clients race to get critical therapies to patients.”
At launch, the Disease Model Finder includes 650 PDX models provided by Charles River, Certis, XenTech, the Lab for Innovated Diagnosis and Experimental Therapeutics (LIDE) and others—a number that is projected to grow quickly as more CROs join the program. By 2022, the platform will include other model systems including organoids, cell-derived xenografts (CDX), syngeneic models, immunoncology models and patient-derived cell lines.
“With so many drugs failing in human clinical trials because they don’t work, it is imperative that we use more predictive preclinical models of disease,” stated Peter Ellman, Certis Oncology CEO. “By combining gene analysis, patient data and tissue profiling data, Scientist.com’s Disease Model Finder increases the odds that researchers are selecting the right Certis models for translational drug development.”