Sabatolimab is a novel immunotherapy with immuno-myeloid activity that targets T-cell immunoglobulin domain and mucin domain-3 (TIM-3) on immune cells and leukemic blasts. It is being evaluated for the treatment of myeloid malignancies in the STIMULUS clinical trial program. The objective of this analysis was to support the sabatolimab dose-regimen selection in hematologic malignancies. A population pharmacokinetic (PopPK) model was fit to patients with solid tumors and hematologic malignancies, which included acute myeloid leukemia, myelodysplastic syndrome (including intermediate-, high-, and very high-risk per Revised International Prognostic Scoring System), and chronic myelomonocytic leukemia. The PopPK model, together with a predictive model of sabatolimab distribution to the bone marrow and binding to TIM-3 was used to predict membrane-bound TIM-3 bone marrow occupancy. In addition, the total soluble TIM-3 (sTIM-3) kinetics and the pharmacokinetic (PK) exposure-response relationship in patients with hematologic malignancies were examined. At intravenous doses above 240 mg Q2w and 800 mg Q4w, we observed linear PK, a plateau in the accumulation of total sTIM-3, and a flat exposure-response relationship for both safety and efficacy. In addition, the model predicted membrane-bound TIM-3 occupancy in the bone marrow was above 95% in over 95% of patients. Therefore, these results support the selection of the 400 mg Q2w and 800 mg Q4w dosing regimens for the STIMULUS clinical trial program.
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http://dx.doi.org/10.1002/psp4.12962 | DOI Listing |
Blood Adv
January 2025
Division of Hematologic Malignancies and Cellular Therapy, Duke University, Duke Cancer Institute, Durham, NC.
Curr Obes Rep
January 2025
Maine Medical Center Research Institute, Maine Medical Center, 81 Research Drive, Scarborough, ME, 04074, USA.
Purpose Of Review: Bone marrow adipose tissue is a distinctive fat depot located within the skeleton, with the potential to influence both local and systemic metabolic processes. Although significant strides have been made in understanding bone marrow adipose tissue over the past decade, many questions remain regarding their precise lineage and functional roles.
Recent Findings: Recent studies have highlighted bone marrow adipose tissue's involvement in continuous cross-talk with other organs and systems, exerting both endocrine and paracrine functions that play a crucial role in metabolic homeostasis, skeletal remodeling, hematopoiesis, and the progression of bone metastases.
Background: Acute myeloid leukemia (AML) is a hematologic malignancy. It is the most common form of acute leukemia among adults. Recent treatment advances have drastically improved outcomes for these diseases, but the overall survival (OS) is still exceptionally low due to the infiltration of leukemic cells in the central nervous system (CNS).
View Article and Find Full Text PDFSupport Care Cancer
January 2025
Department of Inner Medicine II (Hematology/Oncology) and University Cancer Center, Schleswig-Holstein (UCCSH), University Medical Center Schleswig-Holstein (UKSH), Kiel, Germany.
Background: Prior research indicates that engaging in physical activity during chemotherapy can positively influence both physical and psychological parameters in individuals with hematological neoplasms. However, the most effective type, level, intensity, and frequency of exercise remains unclear.
Patients And Methods: We enrolled 53 patients to a clinical trial assessing a partly supervised hybrid training program including both strength and endurance components, commencing at onset of induction therapy (T0) for hematological malignancies, including AML (n = 29), ALL (n = 5), and NHL (n = 19).
Sci Rep
January 2025
Department of Computer and Information Systems, Sadat Academy for Management Sciences, Cairo, Egypt.
Blood cancer is among the critical health concerns among people around the world and normally emanates from genetic and environmental issues. Early detection becomes essential, as the rate of death associated with it is high, to ensure that the rate of treatment success is up, and mortality reduced. This paper focuses on improving blood cancer diagnosis using advanced deep learning techniques like ResNetRS50, RegNetX016, AlexNet, Convnext, EfficientNet, Inception_V3, Xception, and VGG19.
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