Acute Lymphoblastic Leukemia, commonly known as ALL, is a predominant form of cancer during childhood. With the advent of modern healthcare support, the 5-year survival rate has been impressive in the recent past. However, long-term ALL survivors embattle several treatment-related medical and socio-economic complications due to excessive and inordinate chemotherapy doses received during treatment. In this work, we present a model-based approach to personalize 6-Mercaptopurine (6-MP) treatment for childhood ALL with a provision for incorporating the pharmacogenomic variations among patients. Semi-mechanistic mathematical models were developed and validated for i) 6-MP metabolism, ii) red blood cell mean corpuscular volume (MCV) dynamics, a surrogate marker for treatment efficacy, and iii) leukopenia, a major side-effect. With the constraint of getting limited data from clinics, a global sensitivity analysis based model reduction technique was employed to reduce the parameter space arising from semi-mechanistic models. The reduced, sensitive parameters were used to individualize the average patient model to a specific patient so as to minimize the model uncertainty. Models fit the data well and mimic diverse behavior observed among patients with minimum parameters. The model was validated with real patient data obtained from literature and Riley Hospital for Children in Indianapolis. Patient models were used to optimize the dose for an individual patient through nonlinear model predictive control. The implementation of our approach in clinical practice is realizable with routinely measured complete blood counts (CBC) and a few additional metabolite measurements. The proposed approach promises to achieve model-based individualized treatment to a specific patient, as opposed to a standard-dose-for-all, and to prescribe an optimal dose for a desired outcome with minimum side-effects.

In this paper, a mathematical model based on the diffusion of nutrients is developed by considering the physiological changes accompanying the growth of avascular tumour. Avascular tumour growth involves the formation of three different zones namely proliferation, quiescent and necrotic zones. The main processes on which avascular tumour growth depends are: (i) diffusion of nutrients through the tumour from the contiguous tissues, (ii) consumption rate of the nutrients by the cells in the tumour, and (iii) cell death by apoptosis and necrosis. In the model, we consider the tumour to be spherical and the principal nutrients responsible for its growth are oxygen and glucose. By solving for the concentration profiles using the model developed, we are able to compute the radii of the quiescent and necrotic zones as well as that of the tumour. The proposed model is also validated using in vitro tumour growth data and Gompertzian empirical relationship parameters available in the literature. Our model is also successful in capturing the saturated volume of the avascular tumour for different nutrient concentrations at the tumour surface.Dans cetteétude, nousélaborons un modèle mathématique fondé sur la diffusion des nutriments en tenant compte des changements physiologiques qui accompagnent la croissance d'une tumeur avasculaire. La croissance d'une tumeur avasculaire comprend la formation de trois zones différentes,à savoir la zone de prolifération, la zone quiescente et la zone nécrotique. Les principaux processus dont dépend la croissance d'une tumeur avasculaire sont les suivants: (i) la diffusion des nutriments dans la tumeur partant des tissus adjacents, (ii) le taux de consommation des nutriments par les cellules dans la tumeur, et (iii) la mort cellulaire par apoptose et nécrose. Dans le modèle, nous considérons la tumeur commé etant sphérique et les principaux nutriments responsables de sa croissance, l'oxygène et le glucose. En déterminant les profils de concentration au moyen du modèleélaboré, nous sommes en mesure de calculer le radius des zones quiescente et nécrotique, de même que celui de la tumeur. Le modèle proposé estégalement validé au moyen des données sur la croissance des tumeurs in vitro et des paramètres des relations empiriques gompertziennes disponibles dans la documentation. Notre modèle réussitégalementà saisir le volume saturé de la tumeur avasculaire pour différentes concentrations de nutrimentsà la surface de la tumeur.

6-Mercaptopurine (6-MP) is one of the key drugs in the treatment of many pediatric cancers, auto immune diseases and inflammatory bowel disease. 6-MP is a prodrug, converted to an active metabolite 6-thioguanine nucleotide (6-TGN) through enzymatic reaction involving thiopurine methyltransferase (TPMT). Pharmacogenomic variation observed in the TPMT enzyme produces a significant variation in drug response among the patient population. Despite 6-MP’s widespread use and observed variation in treatment response, efforts at quantitative optimization of dose regimens for individual patients are limited. In addition, research efforts devoted on pharmacogenomics to predict clinical responses are proving far from ideal. In this work, we present a Bayesian population modeling approach to develop a pharmacological model for 6-MP metabolism in humans. In the face of scarcity of data in clinical settings, a global sensitivity analysis based model reduction approach is used to minimize the parameter space. For accurate estimation of sensitive parameters, robust optimal experimental design based on D-optimality criteria was exploited. With the patient-specific model, a model predictive control algorithm is used to optimize the dose scheduling with the objective of maintaining the 6-TGN concentration within its therapeutic window. More importantly, for the first time, we show how the incorporation of information from different levels of biological chain-of response (i.e. gene expression-enzyme phenotype-drug phenotype) plays a critical role in determining the uncertainty in predicting therapeutic target. The model and the control approach can be utilized in the clinical setting to individualize 6-MP dosing based on the patient’s ability to metabolize the drug instead of the traditional standard-dose-for-all approach.

Numerous injuries and fatalities in chemical laboratories in the United States over the past few decades have suggested the need to take measures that go beyond mere compliance and toward promoting safer practices. A collaboration between the Center for Innovative and Strategic Transformation of Alkane Resources and Purdue Process Safety and Assurance Center assessed the current safety culture in chemical laboratories at their academic and industrial partners by conducting safety surveys. Key areas of improvement were identified from the responses to the safety surveys, which if addressed can mitigate the severity of safety incidents or prevent them from occurring. The findings indicate that a majority of the respondents from academia conduct comprehensive lab safety trainings (∼80%), have standard operating procedures for potentially hazardous activities (∼90%), regularly discuss safety-related issues during lab group meetings (∼85%), or are involved in routine safety inspections (∼85%). However, fewer of the academic respondents were aware of a database for safety incidents in their departments (∼50%) or utilized a standard safety review process for new experimental setups or modifications to existing setups (∼70%). The results from industry respondents suggest that improvements to commonly used hazard evaluation tools and increased accessibility to comprehensive databases can increase the effectiveness of hazard evaluation processes. Additionally, recommended best practices and guidelines are provided for researchers within the scientific community to develop key safety documentation that will both strengthen the safety culture and improve safety performance in their laboratories. Taken together, this safety initiative highlights the much-needed attention and effort that are beneficial to promote improved safety culture within academic and industrial chemical laboratories.

In the past several years, the U.S. Chemical Safety Board has found an increase in the frequency of laboratory accidents and injuries. An independent survey of industrial and academic laboratories by the authors indicated the shortage of documentation on best practices and lack of free and user-friendly risk assessment tools to be some of the key reasons for the occurrence of safety incidents. Thus, development of a framework to document, assess, and mitigate hazards is a critical starting point for ensuring safe laboratory practices. To address this requirement, Reactive Hazards Evaluation Analysis and Compilation Tool (RHEACT), an online platform to compile and scrutinize hazards-related information, was developed. When planning an experiment, the researchers provide RHEACT: (1) information about the chemicals involved in the reaction, in the form of Safety Data Sheets (SDS), and (2) operating parameters of the reaction. Through the user-supplied SDS, an operational hazard matrix and a chemical compatibility matrix are generated. In addition, adiabatic temperature rise of the reaction is estimated to ensure that the chemistry is within user-controlled bounds. The user is provided with a broad initial evaluation of potential hazards and is notified of safety concerns associated with the reaction before conducting the experiment. We believe that this user-friendly online tool will help engender a safer laboratory working environment.