Teresa A. Bennett

Pharmacological Profiles of Acute Myeloid Leukemia Treatments in Patient Samples by Automated Flow Cytometry: A Bridge to Individualized Medicine

BACKGROUND We have evaluated the ex vivo pharmacology of single drugs and drug combinations in malignant cells of bone marrow samples from 125 patients with acute myeloid leukemia using a novel automated flow cytometry-based platform (ExviTech). We have improved previous ex vivo drug testing with 4 innovations: identifying individual leukemic cells, using intact whole blood during the incubation, using an automated platform that escalates reliably data, and performing analyses pharmacodynamic population models. PATIENTS AND METHODS Samples were sent from 24 hospitals to a central laboratory and incubated for 48 hours in whole blood, after which drug activity was measured in terms of depletion of leukemic cells. RESULTS The sensitivity of single drugs is assessed for standard efficacy (EMAX) and potency (EC50) variables, ranked as percentiles within the population. The sensitivity of drug-combination treatments is assessed for the synergism achieved in each patient sample. We found a large variability among patient samples in the dose-response curves to a single drug or combination treatment. CONCLUSION We hypothesize that the use of the individual patient ex vivo pharmacological profiles may help to guide a personalized treatment selection.

Drug Discovery Testing Compounds in Patient Samples by Automated Flow Cytometry

Functional ex vivo assays that predict a patient’s clinical response to anticancer drugs for guiding cancer treatment have long been a goal, but few have yet proved to be reliable. To address this, we have developed an automated flow cytometry platform for drug screening that evaluates multiple endpoints with a robust data analysis system that can capture the complex mechanisms of action across different compounds. This system, called PharmaFlow, is used to test peripheral blood or bone marrow samples from patients diagnosed with hematological malignancies. Functional assays that use the whole sample, retaining all the microenvironmental components contained in the sample, offer an approach to ex vivo testing that may give results that are clinically relevant. This new approach can help to predict the patients’ response to existing treatments or to drugs under development, for hematological malignancies or other tumors. In addition, relevant biomarkers can be identified that determine the patient’s sensitivity, resistance, or toxicity to a given treatment. We propose that this approach, which better recapitulates the human microenvironment, constitutes a more predictive assay for personalized medicine and preclinical drug discovery.