Medical issues and perspectives

Becton Dickinson (BD) announced a collaboration with Quest Diagnostics to develop, manufacture, and commercialize flow cytometry-based companion diagnostics (CDx) for cancer and other diseases. The financial terms were not disclosed.

BD aims to offer pharmaceutical developers a comprehensive solution for CDx, covering exploratory panel development to the manufacture and distribution of FDA-cleared diagnostic kits. Typically, CDx for therapy selection uses methods like immunohistochemistry, fluorescence in situ hybridization, PCR, next-generation sequencing, and imaging. Flow cytometry, however, can rapidly analyze and sort individual cells, offering insights into an individual's immune response and aiding in patient management.

"This strategic collaboration with BD combines our expertise in developing and validating biomarkers and assays with BD's leadership in flow cytometry to offer a fully integrated solution on a larger scale," stated William Finger, VP and general manager of pharma services for Quest Diagnostics.

In 2023, BD launched the FACSDiscover S8 spectral flow cytometry platform and introduced three- and four-laser additions to the existing five-laser instrument earlier this year. This system enables high-speed cell sorting using both fluorescent and nonfluorescent parameters. Additionally, BD entered a collaboration with Laboratory Corporation of America in 2022 to develop flow cytometry-based CDx.

This partnership aims to enhance the capabilities of flow cytometry in CDx, providing a robust solution for pharma developers in the diagnostic landscape.

Predictive Oncology , a leader in AI-driven drug discovery and biologics, announced the expansion of its AI/ML-driven platform to discover novel biomarkers for predicting patient outcomes and drug response in oncology. This initiative follows the successful results from a retrospective ovarian cancer study with UPMC Magee-Womens Hospital, presented at the 2024 ASCO Annual Meeting. The study developed multi-omic machine learning models that predicted short-term and long-term survival outcomes more accurately than clinical data alone, supporting novel ovarian cancer biomarker discovery.

Arlette H. Uihlein, MD, SVP, highlighted that their platform uses diverse patient samples to predict drug responses accurately and is now applying deep learning for biomarker discovery related to overall survival and drug response. Raymond Vennare, CEO, emphasized the potential for developing a clinical decision support tool and further biomarker discovery for other cancer types through collaborations with biopharmaceutical partners and healthcare networks.

The biomarker discovery market is estimated to be $51.5 billion in 2024. Predictive Oncology released a white paper detailing its biomarker discovery capabilities, accessible at their website.

Predictive Oncology utilizes AI and machine learning to expedite biomarker and drug discovery, benefiting cancer patients globally. Their AI platform, PEDAL, predicts tumor sample responses to drugs with 92% accuracy, supported by a biobank of over 150,000 human tumor samples. They offer comprehensive AI-based drug discovery solutions, complemented by a CLIA lab and GMP facilities, headquartered in Pittsburgh, PA.