Shaping the AML Treatment Landscape:Modeling a Path through Plenty, Uncertainty, and Paucity

The last two decades have identified and characterized heterogeneities arising in the genetic structure of the bone marrow malignancy, acute myeloid leukemia (AML), to partly explain the variation in outcomes among similarly treated patients.[1] In high-income countries, treatment paradigms for AML have now shifted to include conventional chemotherapy and/or small molecule drugs directed against biological targets, deemed disease-defining.[1] [2] [3] Apart from the acute promyelocytic leukemia variant,[4] however, AML remains incurable for a significant number of patients within different disease subgroups. In addition, the incremental survival gain with small molecule drugs is relatively modest,[2] [3] [5] and the costs associated with therapy, supportive care, and disease-monitoring remain considerable. In low-and middle-income countries, financial constraints often render therapies, considered “standard-of-care” in higher income countries, prohibitively expensive.[6] Increasingly, the rarity of biological subtypes of AML[1] and the availability of multiple drugs targeting unique disease sub-types[2] [5] [7] [8] are also beginning to present challenges to the design of contemporaneous clinical trials. To optimize clinical benefits and the cost-effectiveness of therapy to patients and healthcare systems, as well as to address key clinical hypotheses, an innovative approach for hypothesis testing and identifying best therapy is, therefore, required.In recent years, the pharmaceutical industry and regulators have increasingly turned to modeling and simulation to investigate drug–drug interactions,[9] assess the exposure and toxicological impacts of various compounds,[10] [11] and reduce reliance on animal experiments for identifying new products.[12] In contrast, physicians have depended solely on the statistical output of adequately powered clinical trials to guide treatment decisions. The existence of clinical trial data and associated publicly available genomic datasets, along with increasingly sophisticated mathematical and computational methodologies, presents a significant opportunity to make progress in the challenging arena of AML therapeutics. Here, we highlight three problem areas relevant to the therapy or monitoring of AML that could benefit from an integrated biological and mathematical approach.<br/

Shaping the AML Treatment Landscape:Modeling a Path through Plenty, Uncertainty, and Paucity

The last two decades have identified and characterized heterogeneities arising in the genetic structure of the bone marrow malignancy, acute myeloid leukemia (AML), to partly explain the variation in outcomes among similarly treated patients.[1] In high-income countries, treatment paradigms for AML have now shifted to include conventional chemotherapy and/or small molecule drugs directed against biological targets, deemed disease-defining.[1] [2] [3] Apart from the acute promyelocytic leukemia variant,[4] however, AML remains incurable for a significant number of patients within different disease subgroups. In addition, the incremental survival gain with small molecule drugs is relatively modest,[2] [3] [5] and the costs associated with therapy, supportive care, and disease-monitoring remain considerable. In low-and middle-income countries, financial constraints often render therapies, considered “standard-of-care” in higher income countries, prohibitively expensive.[6] Increasingly, the rarity of biological subtypes of AML[1] and the availability of multiple drugs targeting unique disease sub-types[2] [5] [7] [8] are also beginning to present challenges to the design of contemporaneous clinical trials. To optimize clinical benefits and the cost-effectiveness of therapy to patients and healthcare systems, as well as to address key clinical hypotheses, an innovative approach for hypothesis testing and identifying best therapy is, therefore, required.In recent years, the pharmaceutical industry and regulators have increasingly turned to modeling and simulation to investigate drug–drug interactions,[9] assess the exposure and toxicological impacts of various compounds,[10] [11] and reduce reliance on animal experiments for identifying new products.[12] In contrast, physicians have depended solely on the statistical output of adequately powered clinical trials to guide treatment decisions. The existence of clinical trial data and associated publicly available genomic datasets, along with increasingly sophisticated mathematical and computational methodologies, presents a significant opportunity to make progress in the challenging arena of AML therapeutics. Here, we highlight three problem areas relevant to the therapy or monitoring of AML that could benefit from an integrated biological and mathematical approach.<br/

The long shadow of socioeconomic deprivation over the modern management of acute myeloid leukemia – time to unravel the challenges

Abstract Biological and non-biological variables unrelated to acute myeloid leukemia (AML) preclude standard therapy in many settings, with “real world” patients under-represented in clinical trials and prognostic models. Here, using a case-based format, we illustrate the impact that socioeconomic and anthropogeographical constraints can have on optimally managing AML in 4 different healthcare systems. The granular details provided, emphasize the need for the development and targeting of socioeconomic interventions that are commensurate with the changing landscape of AML therapeutics, in order to avoid worsening the disparity in outcomes between patients with biologically similar disease

The long shadow of socioeconomic deprivation over the modern management of acute myeloid leukemia: time to unravel the challenges

Biological and non-biological variables unrelated to acute myeloid leukemia (AML) preclude standard therapy in many settings, with “real world” patients under-represented in clinical trials and prognostic models. Here, using a case-based format, we illustrate the impact that socioeconomic and anthropogeographical constraints can have on optimally managing AML in 4 different healthcare systems. The granular details provided, emphasize the need for the development and targeting of socioeconomic interventions that are commensurate with the changing landscape of AML therapeutics, in order to avoid worsening the disparity in outcomes between patients with biologically similar disease

Adoptive transfer of cytomegalovirus-specific CTL to stem cell transplant patients after selection by HLA–peptide tetramers

Stem cell transplantation is used widely in the management of a range of diseases of the hemopoietic system. Patients are immunosuppressed profoundly in the early posttransplant period, and reactivation of cytomegalovirus (CMV) remains a significant cause of morbidity and mortality. Adoptive transfer of donor-derived CMV-specific CD8(+) T cell clones has been shown to reduce the rate of viral reactivation; however, the complexity of this approach severely limits its clinical application. We have purified CMV-specific CD8(+) T cells from the blood of stem cell transplant donors using staining with HLA-peptide tetramers followed by selection with magnetic beads. CMV-specific CD8(+) cells were infused directly into nine patients within 4 h of selection. Median cell dosage was 8.6 x 10(3)/kg with a purity of 98% of all T cells. CMV-specific CD8(+) T cells became detectable in all patients within 10 d of infusion, and TCR clonotype analysis showed persistence of infused cells in two patients studied. CMV viremia was reduced in every case and eight patients cleared the infection, including one patient who had a prolonged history of CMV infection that was refractory to antiviral therapy. This novel approach to adoptive transfer has considerable potential for antigen-specific T cell therapy