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Leukemia is an immediately life-threatening cancer wherein immature blood cells are overproduced, accumulate in the bone marrow (BM) and blood and causes immune and blood system failure. Treatment with chemotherapy can be intensive or nonintensive and can also be life-threatening since only relatively few patient-specific and leukemia-specific factors are considered in current protocols. We have already presented a mathematical model for one intensive chemotherapy cycle with intravenous (i.v.) daunorubicin (DNR), and cytarabine (Ara-C). This model is now extended to nonintensive subcutaneous (SC) Ara-C and for a standard intensive chemotherapy course (four cycles), consistent with clinical practice. Model parameters mainly consist of physiological patient data, indicators of tumor burden and characteristics of cell cycle kinetics. A sensitivity analysis problem is solved and cell cycle parameters are identified to control treatment outcome. Simulation results using published cell cycle data from two acute myeloid leukemia patients are presented for a course of standard treatment using intensive and nonintensive protocols. The aim of remission-induction therapy is to debulk the tumor and achieve normal BM function; by treatment completion, the total leukemic population should be reduced to at most 10(9) cells, at which point BM hypoplasia is achieved. The normal cell number should be higher than that of the leukemic, and a 3-log reduction is the maximum permissible level of population reduction. This optimization problem is formulated and solved for the two patient case studies. The results clearly present the benefits from the use of optimization as an advisory tool for treatment design.

Highlights(1) The building blocks of a biomedical systems modeling framework are presented (2) Interactions between building blocks are reviewed; two system types are described (3) An example of a laboratory system type is described: artificial blood production (4) An example of a patient system type is discussed: leukemia treatment optimization (5) Other biomedical applications are briefly introduced as part of the framework 2 M. Fuentes-Garí et al. AbstractWe review the key building blocks of a design framework for modeling and optimizing biomedical systems under development in the Biological Systems Engineering Laboratory and the Centre for Process Systems Engineering at Imperial College. The framework features the following components: (i) in vitro environment, where model parameters can be obtained and new setups can be tested; (ii) in silico environment, including a simulation module for representing relevant physical or biological processes, and an optimization module, for calculating of improved in vitro or in vivo outcomes; (iii) in vivo environment, from which organ and patient-specific parameters are collected and which can also implement personalized suggestions for improved outcomes. Two applications in the area of healthy and diseased blood are thoroughly discussed to exemplify the framework's characteristics. We discuss progress in the different areas and the way in which they are connected and finally propose a hybrid in vitro/in silico/in vivo platform. Keywords

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This study describes the pharmacokinetic (PK) and pharmacodynamic (PD) profile of N-(5-(4-(5-(((2R,6S)-2,6-dimethylmorpholino)methyl)oxazol-2-yl)-1H-indazol-6-yl)-2-methoxypyridin-3-yl)methanesulfonamide (GSK2292767A), a novel low-solubility inhaled phosphoinositide 3-kinase delta (PI3Kd) inhibitor developed as an alternative to 2-(6-(1H-indol-4-yl)-1H-indazol-4-yl)-5-((4-isopropylpiperazin-1-yl)methyl)oxazole (nemiralisib), which is a highly soluble inhaled inhibitor of PI3Kd with a lung profile consistent with once-daily dosing. GSK2292767A has a similar in vitro cellular profile to nemiralisib and reduces eosinophilia in a murine PD model by 63% (n 5 5, P , 0.05). To explore whether a low-soluble compound results in effective PI3Kd inhibition in humans, a first time in human study was conducted with GSK2292767A in healthy volunteers who smoke. GSK2292767A was generally well tolerated, with headache being the most common reported adverse event. PD changes in induced sputum were measured in combination with drug concentrations in plasma from single (0.05-2 mg, n 5 37), and 14-day repeat (2 mg, n 5 12) doses of GSK2292767A. Trough bronchoalveolar lavage (BAL) for PK was taken after 14 days of repeat dosing. GSK2292767A displayed a linear increase in plasma exposure with dose, with marginal accumulation after 14 days. Induced sputum showed a 27% (90% confidence interval 15%, 37%) reduction in phosphatidylinositol-trisphosphate (the product of phosphoinositide 3-kinase activation) 3 hours after a single dose. Reduction was not maintained 24 hours after single or repeat dosing. BAL analysis confirmed the presence of GSK2292767A in lung at 24 hours, consistent with the preclinical lung retention profile. Despite good lung retention, target engagement was only present at 3 hours. This exposure-response disconnect is an important observation for future inhaled drug design strategies considering low solubility to drive lung retention.