AbstractNovel immune-cellular target therapies have been actively developed and introduced in the real-world treatment of acute lymphoblastic leukemia (ALL). However, we are still using multi-agent chemotherapy to reduce the initial tumor burden and facing many relapsed or refractory (R/R) patients with poor survival outcomes. In this study, we measured the ex vivo sensitivity of patient-derived cells to as many as 21 different anti-cancer drugs and assessed their prognostic utility. The results confirmed a strong utility of the drug sensitivities in predicting clinical outcomes. Out of 37 ALL patients who participated, we performed ex vivo DS analysis on 27 patients (9 Ph-negative, 14 Ph-positive, and 4 T-ALL at diagnosis (n=17) and at relapse (n=10)) using bone marrow aspirates. Briefly, the isolated blast cells were incubated for 72 hours with various concentrations of up to 21 anti-cancer drugs, and changes in viability were measured using the Alamar Blue assay. For each drug, we calculated the individual patient’s drug sensitivity in terms of the three metrics—IC50, area under the curve (AUC), and Emax (the remaining viability at the highest concentrations). Smaller values of IC50, AUC, and Emax correspond to high drug sensitivities. After sample acquisition, all patients received one of the following therapies: Modified hyper-CVAD (cyclophosphamide, vincristine, doxorubicin, dexamethasone, n=6) plus tyrosine kinase inhibitors (n=8) or L-asparaginase (n=2), inotuzumab ozogamicin (n=3), tyrosine kinase inhibitor (TKI) alone (n=3), blinatumomab (n=2), chimeric antigen receptor T-cells (CAR-T, n=1), and others (n=2). Complete response was achieved in 24 patients (89%), and minimal residual disease (MRD) was observed in 16 (67%) among the responders. During the follow-up, with median of 22 months, there were 3 refractory and 2 relapsed patients, 4 succumbed to death in remission, and 3 died due to leukemia progression. Given the various disease subtypes and treatment modalities, we focused on the patients with available DS analysis results treated with modified hyper-CVAD +/- imatinib/L-asparaginase (n=16) for further analysis. Upon evaluating the predictive utility of the drug sensitivity metrics, we found that the Emax of cyclophosphamide or other alkylating agents (melphalan, busulfan or ifosfamide) was effective (ROC-AUC of 1.00, n=6) in predicting early disease-progression (<3 months) of Ph+ ALL. On the other hand, the Emax of decitabine was effective (ROC-AUC of 1.00, n=5) in predicting early disease progression of Ph- B-ALL. For T-ALL, the Emax of multiple drugs—decitabine, alkylating agents including cyclophosphamide, and mitoxantrone—were effective in predicting early disease progression (ROC-AUC of 1.00, n=2). Furthermore, the unsupervised clustering of the drug AUCs was effective in predicting MRD positivity (ROC-AUC of 0.85, n = 27). In conclusion, we report that our proprietary ex vivo drug sensitivity platform may have clinical utility in identifying ineffective therapy for ALL patients across multiple subtypes and/or settings.Citation Format: Sung-Soo Park, Sungwon Lim, Seunghyok Ham, Seongjun Lee, Sesun Park, Hyoju Yi, Seok Lee, Jae-Ho Yoon, Jamin Koo. A study on the relationship between ex vivo drug sensitivity and clinical outcome of acute lymphoblastic leukemia [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Functional and Genomic Precision Medicine in Cancer: Different Perspectives, Common Goals; 2025 Mar 11-13; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2025;85(5 Suppl):Abstract nr B002.

05 Nov 2024·Blood

A Study on the Relationship between Ex Vivo Drug Sensitivity and Clinical Outcome of Acute Lymphoblastic Leukemia

Author: Yoon, Jae-Ho ; Lim, Sungwon ; Koo, Jamin ; Park, Sesun ; Park, Sung-Soo ; Ham, Seunghyeok ; Lee, Seok ; Lee, Seongjoon ; Yi, Hyoju

Novel immune-cellular target therapies have been actively developed and introduced in the real-world treatment of acute lymphoblastic leukemia (ALL). However, we are still using multi-agent chemotherapy to reduce the initial tumor burden and facing many relapsed or refractory (R/R) patients with poor survival outcomes. Conventional risk factors and molecular cytogenetic profiles substantially influence treatment selection, but the expected response to a specific treatment based on the data from a large group of patients with a similar mutational profile is not always equal to the actual response observed on an individual basis. Previous studies suggest that ex vivo drug sensitivity (DS) analysis enables more accurate prediction of individual responses, allowing personalized treatment of lymphoma and acute myeloid leukemia (AML). In this study, we measured the ex vivo sensitivity of patient-derived cells to as many as 21 different anti-cancer drugs and assessed their prognostic utility. The results confirmed a strong utility of the drug sensitivities in predicting clinical outcomes.Out of 37 ALL patients who participated, we performed ex vivo DS analysis on 27 patients (9 Ph-negative, 14 Ph-positive, and 4 T-ALL at diagnosis (n=17) and at relapse (n=10)) using bone marrow aspirates. The reasons behind not being able to conduct the DS analysis were insufficient number of cancer cells in the aspirates (90%) and delayed shipping (10%). Except for those cases, we were able to conduct DS analysis using the previous reported media and protocol for AML. Briefly, the isolated blast cells were incubated for 72 hours with various concentrations of up to 21 anti-cancer drugs, and changes in viability were measured using the Alamar Blue assay. For each drug, we calculated the individual patient's drug sensitivity in terms of the three metrics-IC50 (the drug concentration to inhibit cell growth by 50%), area under the curve (AUC, area under the dose vs viability curve), and Emax (the remaining viability at the highest drug concentrations tested). Smaller values of IC50, AUC, and Emax correspond to high drug sensitivities.After sample acquisition, all patients received one of the following therapies: Modified hyper-CVAD (cyclophosphamide, vincristine, doxorubicin, dexamethasone, n=6) plus tyrosine kinase inhibitors (n=8) or L-asparaginase (n=2), inotuzumab ozogamicin (n=3), tyrosine kinase inhibitor (TKI) alone (n=3), blinatumomab (n=2), chimeric antigen receptor T-cells (CAR-T, n=1), and others (n=2). Complete response was achieved in 24 patients (89%), and minimal residual disease (MRD) was observed in 16 (67%) among the responders. During the follow-up, with median of 22 months, there were 3 refractory and 2 relapsed patients, 4 succumbed to death in remission, and 3 died due to leukemia progression.Given the various disease subtypes and treatment modalities, we focused on the patients with available DS analysis results treated with modified hyper-CVAD +/- imatinib/L-asparaginase (n=16) for further analysis. Upon evaluating the predictive utility of the drug sensitivity metrics, we found that the Emax of cyclophosphamide or other alkylating agents (melphalan, busulfan or ifosfamide) was effective (ROC-AUC of 1.00, n=6) in predicting early disease-progression (<3 months) of Ph+ ALL. On the other hand, the Emax of decitabine was effective (ROC-AUC of 1.00, n=5) in predicting early disease progression of Ph- B-ALL. For T-ALL, the Emax of multiple drugs-decitabine, alkylating agents including cyclophosphamide, and mitoxantrone-were effective in predicting early disease progression (ROC-AUC of 1.00, n=2). Furthermore, the unsupervised clustering of the drug AUCs was effective in predicting MRD positivity (ROC-AUC of 0.85, n = 27).In conclusion, we report that our proprietary ex vivo drug sensitivity platform may have clinical utility in identifying ineffective therapy for ALL patients across multiple subtypes and/or settings. DS analysis results of single drugs were able to prediction clinical outcome of modified hyper-CVAD +/- imatinib/L-asparaginase, which consists of at least four chemotherapeutic agents. Emax, which correlates to the proportion of the drug-resistant cancer cells, was the most useful in discriminating early disease progression, coinciding with our previous observation in AML.

02 Nov 2023·Blood

Prognostic Utility of the Patient-Derived AML Cells' Ex Vivo Drug Sensitivity Results

Author: Lim, Sungwon ; Park, Sung-Soo ; Song, Edward ; Kim, Heeje ; Park, Silvia ; Lee, Gunjae ; Lee, Junyoung ; Lee, Seongjoon ; Ham, Seunghyeok ; Cho, Byoung Sik ; Koo, Jamin ; Choi, Gyucheol ; Kim, Kwan Hyun ; Park, Sesun

Genomic mutational profiles substantially influence selection of the treatment as they impact drug responses. However, the expected response to a specific treatment based on the data from a large group of the patients with the similar mutational profile is not always equal to the actual response observed at an individual basis. In this study, we measured ex vivo sensitivity of the patient-derived AML cells to 21 different anti-cancer drugs and assessed their prognostic utility.The ex vivo drug sensitivity analysis was performed using the bone marrow (BM) aspirates of 45 out of 58 AML patients (78%), which contained sufficient number of live cancer cells. The isolated blast cells were incubated for 72 hours with various concentrations of the 21 drugs used to treat hematologic malignancies, and changes in viability were measured using the Alamar Blue assay. For each drug, we calculated the individual patient's drug sensitivity in terms of the three metrics-IC 50 (the drug concentration to inhibit cell population by 50%), area under the curve (AUC, area under the viability curve for a cell population over the tested drug concentration range), and E max (the fraction of viable cells at the highest drug concentrations tested). In the context of drug potency, smaller values of IC 50 AUC and E max correspond to high drug sensitivities.After sample acquisition, 14 out of 45 patients did not receive treatment while the remaining patients received the following treatments: Venetoclax plus hypomethylating agent (VEN+HMA) in either the newly diagnosed (ND) (n=9) or relapsed/refractory (R/R) setting (n=6), Anthracycline plus cytarabine(AraC) based induction (n=8) or reinduction (n=4), and others (n=4). Expectedly, the values of AUC, IC 50 and E max differed substantially across the cohort for all 21 drugs, in alignment with unequal responses and survival across the patients treated with the same regimen; the range of E max, for example, spanned 0 to 100% for 17 of the 21 drugs. We confirmed that the interpersonal differences in the drug sensitivity metrics were at least 8-fold greater than the variability observed across replicate experiments performed using the leukemia cell line HL60.Given the various disease setting and treatment modalities, we focused on the patients receiving the VEN+HMA (n=15) and Anthra + AraC based (re)induction (n=12) for further analysis. Upon evaluating the predictive utility of the drug sensitivity metrics, we found that the E max of VEN was the most effective in predicting survival after the administration of VEN+HMA, with an ROC-AUC of 0.84. The median E max of VEN was significantly higher (38% vs 17%) among the patients who died within 2 months of the first administration (n = 4) compared to those who survived (n = 11). When stratified into the high vs low risk subgroups based on the E max of VEN, overall survival of the low risk subgroup was significantly ( P=0.0025) superior with hazard ratio of 8.9 (95% CI, 0.7 - 108.9). On the other hand, the AUC of VEN exhibited the strongest utility in predicting the response (CR(i)) to VEN+HMA therapy, with an ROC-AUC of 0.72. While the E max or AUC values of the HMA drugs did not show any strong correlation to the treatment outcomes. We observed the similar tendency for other treatments including Anthracycline + AraC; E max of idarubicin (IDA) was significantly higher (21% vs 3+1%) for the patient who died (n = 1) within 100 days of the regimen administration than those who survived (n = 7). In contrast, E max of ARA was non-discriminant (21% vs 15+10%) although the values were in general much lower than those observed for the HMA drugs. ROC-AUC of survival and response prediction was 1.00 based on E max of IDA, however, a bigger cohort is needed to confirm the statistical significance of the observed utility.In conclusion, we report that our proprietary ex vivo drug sensitivity platform may have clinical utility in selecting the best-fitting therapy for AML patients in an individualized manner. Interestingly, different metrics representing the ex vivo drug sensitivity had disparate utility in prediction the clinical outcome. E max, which correlates to the proportion of the drug-resistant cancer cells, was particularly useful in discriminating overall survival in patients treated with VEN + HMA or Anthracycline + AraC regimens, while AUC showed promise in predicting response specifically in patients treated with VEN + HMA.

News (Medical) associated with ImpriMed, Inc.

07 Apr 2025

·www.mobihealthnews.com

Caris Life Sciences secures $168M for precision medicine platform

Biotechnology and precision medicine company Caris Life Sciences announced it raised $168 million in growth capital funding. Caris Life Sciences has now raised $1.86 billion in capital since 2018. Braidwell LP led the round with participation from new investors Perceptive Advisors, Woodline and Ghisallo. Millennium Management and First Light Asset Management also participated in the round. WHAT IT DOES Caris is involved in pathology and molecular profiling to diagnose and treat cancerous tissues. It uses molecular science AI and machine learning algorithms to analyze cancer to help guide physicians in making treatment decisions. The company will use the money to grow its precision medicine platform and scale its reach. "This raise will help us bring our market-leading science and technologies to as many patients as possible and further our goal of revolutionizing precision medicine," David Halbert, chairman, founder and CEO of Caris, said in a statement. "We plan to unlock the full potential of precision medicine by comprehensively interrogating cancer at the molecular level and enabling the delivery of transformative applications of molecular science." MARKET SNAPSHOT In 2023, ConcertAI announced it expanded its partnership with Caris Life Sciences. The two companies created a database to generate insights to advance precision medicine, clinical trial management and therapeutic development. The partners developed a database that leverages both companies' clinical, molecular and multimodal data aimed at allowing academics and biopharma researchers to acquire insights for oncology-focused precision medicine, clinical trial management and therapeutic development. Other companies involved in precision medicine for cancer include ImpriMed, which in 2024 expanded its services to include human oncology with the aim of providing drug-response predictions for routine blood cancers, such as newly diagnosed multiple myeloma and acute myeloid leukemia. ImpriMed's human precision medicine services focus on complex blood cancers, using genomic analysis, machine learning and ex vivo drug sensitivity testing. In 2023, Pfizer announced a multiyear strategic alliance with Tempus to use AI and machine learning to inform drug discovery and development in oncology. Pfizer uses Tempus' library of de-identified data to increase therapeutic development in oncology. Additionally, it will use Tempus' AI-driven companion diagnostic tools and clinical trial-matching program to bolster therapeutic research and development.

Clinical Study

23 Sep 2024

·www.mobihealthnews.com

ImpriMed unveils cancer treatment forecast technology

ImpriMed, a precision medicine company, announced that it has expanded its services to include human oncology. The aim is to provide drug-response predictions for routine blood cancers such as newly diagnosed multiple myeloma and acute myeloid leukemia. ImpriMed's human precision medicine services will set their sights on complex blood cancers via a combination of genomic analysis, ex vivo drug sensitivity testing and machine learning. Data from the company's new research for naive non-Hodgkin lymphoma treatment outcomes will be presented at the EHA-SfPM meeting in Copenhagen, Denmark, September 25-27. "The expansion of ImpriMed’s precision medicine services from veterinary to human oncology is a pivotal milestone in our mission to transform cancer treatment," Dr. Sungwon Lim, ImpriMed chief executive officer, said in a statement. "By empowering oncologists and researchers to leverage AI-driven technology to predict treatment outcomes, every patient can receive truly personalized therapy. With our expansion into contract research organization services, we look forward to supporting the development of novel cancer therapies and more personalized treatments, aiming to bring hope to many more patients in their cancer journeys." THE LARGER TREND In August, ImpriMed announced the publication of research on a novel cell-sizing method for feline lymphomas in Veterinary Sciences. Data from the research revealed that by improving the precision of cell-size evaluation, ImpriMed’s technique can possibly transform veterinary oncology and give more dependable prognostic insights and improve treatment planning and patient outcomes. In May, the company launched ImpriMed Drug Response Predictions, an AI service that brings personalized anticancer drug response projections for canine patients with lymphoma or leukemia. DRP is an addendum to the company’s personalized prediction profile, which features an “immunoprofile” report that gives clonality and immunophenotype data.

23 Sep 2024

·www.businesswire.com

ImpriMed Unveils Cancer Treatment Prediction Technology at EHA-SfPM Meeting, Expands AI-Driven Precision Medicine Services from Pets to Humans

MOUNTAIN VIEW, Calif.--( BUSINESS WIRE )-- EHA-SfPM – ImpriMed , a leading functional precision medicine company focused on leveraging artificial intelligence to improve cancer treatment, today announced the expansion of its precision medicine services into human oncology. Building on its success in veterinary oncology, ImpriMed’s pioneering human oncology services will provide drug response predictions for common blood cancers, including newly diagnosed multiple myeloma and acute myeloid leukemia. The company’s transformative new research for naïve non-Hodgkin lymphoma treatment outcomes will be unveiled at the upcoming EHA-SfPM Precision Medicine Meeting in Copenhagen, Denmark, from September 25-27, 2024. ImpriMed Human Oncology Services Precision medicine enables personalized therapy solutions tailored to each patient’s unique genetic and biological profile, transforming clinical treatment approaches and improving patient outcomes. ImpriMed’s human precision medicine services will focus on complex blood cancers through an innovative combination of genomic analysis, ex vivo drug sensitivity testing, and/or machine learning. Initial services include: Newly Diagnosed Multiple Myeloma (NDMM) : ImpriMed’s NDMM software-as-a-medical device utilizes AI and patient data to predict treatment outcomes and the probability of early disease progression without the need for biological samples. Acute Myeloid Leukemia (AML) : ImpriMed’s technology evaluates drug sensitivity test results for 21 anticancer drugs, enabling predictions of the patient’s drug responses and survival outcomes to optimize individual treatment plans. Non-Hodgkin Lymphoma (NHL) : ImpriMed’s novel approach to tackling NHL runs ex vivo drug sensitivity tests to accurately predict treatment outcomes, facilitating more precise treatment protocols. EHA-SfPM Precision Medicine Meeting Participation At EHA-SfPM, ImpriMed CEO Dr. Sungwon Lim will kick off the company’s expansion into human cancer care with a poster presentation titled "Predicting treatment-specific outcomes for naïve non-Hodgkin lymphoma using ex vivo drug sensitivity analyses." This groundbreaking study outlines the potential of ex vivo drug sensitivity testing in predicting treatment outcomes and guiding therapeutic decisions for naïve NHL patients, potentially improving survival outcomes. The presentation marks a significant advancement in ImpriMed’s successful application of machine learning model development for personalized drug response and prognosis predictions and ex vivo drug sensitivity analyses to human cancer care. The company also previously presented the prognostic utility of patient-derived AML cells’ ex vivo drug sensitivity results at the 2023 American Society of Hematology Annual Conference. “The expansion of ImpriMed’s precision medicine services from veterinary to human oncology is a pivotal milestone in our mission to transform cancer treatment,” said Lim. “By empowering oncologists and researchers to leverage AI-driven technology to predict treatment outcomes, every patient can receive truly personalized therapy. With our expansion into contract research organization services, we look forward to supporting the development of novel cancer therapies and more personalized treatments, aiming to bring hope to many more patients in their cancer journeys.” ImpriMed is also a proud sponsor of EHA-SfPM alongside other leading pharmaceutical companies. The event, co-organized by the European Hematology Association (EHA) and the Society for Functional Precision Medicine (SfPM), will bring together global experts to discuss the future of predictive diagnostics and drug development for both liquid and solid tumors, underscoring ImpriMed’s commitment to advancing precision medicine in hematological malignancy. The company also plans to broaden its contract research organization (CRO) services, offering pharmaceutical companies access to ImpriMed’s cutting-edge live-cell analysis platform to evaluate the efficacy of new drug compounds on their target patients’ live cancer cells. Meet with ImpriMed at EHA-SfPM To schedule an in-person meeting with ImpriMed at EHA-SfPM, interested parties can fill out a meeting request form here . For more information about ImpriMed's expansion into human oncology, participation at EHA-SfPM, and CRO services, please visit www.imprimedicine.com/oncology . About ImpriMed ImpriMed, founded in 2017 in Silicon Valley, is a leading precision medicine startup transforming cancer treatment with artificial intelligence. The company’s pioneering drug response prediction technology helps reduce costs, accelerate treatment, enhance efficacy, and improve the quality of life for patients. To date, the company’s technology has been deployed across more than 40 U.S. states, Canada, England, France, and South Korea, treating 7,500+ canine and feline blood cancer patients as of 2024. ImpriMed is now poised to extend its groundbreaking AI-driven approach to human healthcare, redefining the future of oncology treatment with personalized, effective solutions. For additional information, visit www.imprimedicine.com .

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