(19MB057) (13MB048) Diagnostic for Predicting Response to Therapies in Multiple Myeloma

Multiple Myeloma (MM) is an incurable but treatable cancer, where patients are prescribed a combination of drugs in response to successive relapses. Our novel digital imaging algorithm diagnostic uses continuous live brightfield microscopy to assess pa…

Multiple Myeloma (MM) is an incurable but treatable cancer, where patients are prescribed a combination of drugs in response to successive relapses. Our novel digital imaging algorithm diagnostic uses continuous live brightfield microscopy to assess patient derived MM cells’ response to therapeutic agents in varying combinations and concentrations at multiple time points to support physician’s choice of therapy to produce the longest duration of remission.

Abstract

  • NIH’s SEER reported 32,720 new cases, 12,830 deaths and 141,000 individuals living with Multiple Myeloma (MM) in the US in 2020. In the current standard of care, clinicians have seven drugs, and nine possible 3-4-drug combination regimens, to choose from in the first round of treatment. Based on overall progression free survival in MM, the average patient relapses once every two years, upon which a bone marrow biopsy is requested along with diagnostic and prognostic tests. Upon relapse, the number of drugs rises to sixteen, and therapeutic options continue to increase for relapsed patients who are sent to clinical trials. Effective treatment regimens may result in superior clinical outcomes because ineffective therapies may allow tumors to grow and evolve, as well as burdening the patients with unnecessary toxicities and financial cost of ineffective drugs. Unfortunately, there are no predictive tests available for choice of therapy in MM.
  • The market for drug response diagnostics is attractive as evidenced by the products offered by Foundation Medicine and Quest Diagnostics.
  • Moffitt’s technology can test between 32 and 127 drugs/combinations over a range of concentrations from a standard of care biopsy, with results generated in under a week to predict therapeutic agent(s) (or combination) to maximize disease remission. Additionally, this technology has been used, in collaboration with partners in Pharmaceutical Industry, to conduct virtual clinical trials, where patient-derived samples were screened with experimental drugs, in order to assess clinical efficacy, as well as identify biomarkers for response. When validated in an observational predictive clinical study from 23 patients, it predicted treatment responses and accurately classified them as per International Myeloma Working Group (IMWG) response stratification.

Wesbite

https://moffitt.org/research-science/academic-and-industry-partnerships/office-of-innovation/available-technologies/diagnostics/19mb057-13mb048-diagnostic-for-predicting-response-to-therapies-in-multiple-myeloma/