Merck KGaA inks cancer metabolism drug discovery alliance with Selvita

Merck KGaA SVP Andree Blaukat

Merck KGaA has teamed up with Selvita to discover small molecule drugs against multiple oncology indications. The alliance builds on an earlier two-year research collaboration into the discovery of enzyme inhibitors to regulate metabolic processes in cancer cells.

Selvita started helping Merck KGaA with its oncology research ambitions in 2013, at which time the partners were focused on targeting the metabolic pathways that support the growth and spread of cancer cells. Programs initiated in the collaboration transitioned from discovery to preclinical earlier this year. And with the original deal coming to an end last month, Merck KGaA has now entered into a new three-year alliance to continue the early-stage research collaboration and set the terms for the ongoing development of the lead candidates.

The partners are pooling their target validation, bioinformatics, medicinal chemistry and toxicology skills for a jointly funded research drive that runs up to lead identification, after which Merck KGaA will take over. Selvita is in line to pick up milestone payments as Merck KGaA advances drugs discovered in the alliance, which is targeting both solid and hematological cancers. Details of specific indications are yet to emerge. But whatever progress the partners have made over the past two years was clearly significant enough to encourage Merck KGaA to extend the deal. 

"We are making strong progress in the area of cancer metabolism," Merck KGaA SVP Andree Blaukat said in a statement. Merck KGaA is far from alone in thinking it is making advances in the field. This year, Celgene ($CELG) further validated the cancer metabolism work Agios Pharmaceuticals ($AGIO) is doing by striking an $80 million deal for a preclinical candidate. And Bayer picked up an early-stage tumor metabolism program from Sweden's Sprint Bioscience for up to $210 million. Each company is betting they can have an effect on cancer by tinkering with the metabolic machinery of tumors.

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