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Agent-based modeling: a systematic assessment of use cases and requirements for enhancing pharmaceutical research and development productivity.

ABSTRACT: A crisis continues to brew within the pharmaceutical research and development (R&D) enterprise: productivity continues declining as costs rise, despite ongoing, often dramatic scientific and technical advances. To reverse this trend, we offer various suggestions for both the expansion and broader adoption of modeling and simulation (M&S) methods. We suggest strategies and scenarios intended to enable new M&S use cases that directly engage R&D knowledge generation and build actionable mechanistic insight, thereby opening the door to enhanced productivity. What M&S requirements must be satisfied to access and open the door, and begin reversing the productivity decline? Can current methods and tools fulfill the requirements, or are new methods necessary? We draw on the relevant, recent literature to provide and explore answers. In so doing, we identify essential, key roles for agent-based and other methods. We assemble a list of requirements necessary for M&S to meet the diverse needs distilled from a collection of research, review, and opinion articles. We argue that to realize its full potential, M&S should be actualized within a larger information technology framework--a dynamic knowledge repository--wherein models of various types execute, evolve, and increase in accuracy over time. We offer some details of the issues that must be addressed for such a repository to accrue the capabilities needed to reverse the productivity decline.

SUBMITTER: Hunt CA

PROVIDER: S-EPMC3739932 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundUltrasound enhancing agents (UEAs) are routinely used to improve transthoracic echocardiographic (TTE) image quality, yet anticipation of UEA need is a barrier to their use.MethodsStructured report data from 171,509 consecutive TTE studies in 97,515 patients who underwent TTE imaging from January 26, 2000, to September 20, 2018, were analyzed. Trends in UEA use and suboptimal image quality were examined. Among outpatients (92,291 TTE examinations, n = 56,479), the data set was randomly split into a 75% derivation sample and a 25% validation sample. Logistic regression was used to model the composite of either UEA receipt or suboptimal image quality (two or more nonvisualized segments) using only variables available at the start of the TTE examination. Model performance was tested in the validation sample.ResultsA total of 4,444 TTE examinations (2.6%) in 3,827 patients (3.9%) involved UEAs, and 28,468 TTE examinations (16.6%) in 21,994 patients (22.5%) were suboptimal. UEA use increased over the observation period. Among TTE studies with suboptimal image quality, UEA use was lower in women (P < .0001). Among outpatients referred for TTE imaging, older age, greater weight, and higher heart rate best predicted UEA use or suboptimal image quality. Model performance in the validation sample was excellent (C statistic = 0.74 [95% CI, 0.73-0.75]; calibration slope = 1.11 [95% CI, 1.06-1.15]).ConclusionsIn this large, single-center, retrospective study, UEA use remained substantially below rates of suboptimal image quality, despite increases over time. Among outpatients, a simple prediction rule using three routinely collected variables available before TTE image acquisition predicted potential benefit from UEAs with high accuracy. If confirmed in other cohorts, this rule may be used to identify patients who may benefit from intravenous placement for UEA administration before TTE image acquisition, thus potentially improving work-flow efficiency.

Project description:Multiple myeloma, the second most common hematological cancer, is currently incurable due to refractory disease relapse and development of multiple drug resistance. We and others recently established the biophysical model that myeloma initiating (stem) cells (MICs) trigger the stiffening of their niches via SDF-1/CXCR4 paracrine; The stiffened niches then promote the colonogenesis of MICs and protect them from drug treatment. In this work we examined in silico the pharmaceutical potential of targeting MIC niche stiffness to facilitate cytotoxic chemotherapies. We first established a multi-scale agent-based model using the Markov Chain Monte Carlo approach to recapitulate the niche stiffness centric, pro-oncogenetic positive feedback loop between MICs and myeloma-associated bone marrow stromal cells (MBMSCs), and investigated the effects of such intercellular chemo-physical communications on myeloma development. Then we used AMD3100 (to interrupt the interactions between MICs and their stroma) and Bortezomib (a recently developed novel therapeutic agent) as representative drugs to examine if the biophysical properties of myeloma niches are drugable. Results showed that our model recaptured the key experimental observation that the MBMSCs were more sensitive to SDF-1 secreted by MICs, and provided stiffer niches for these initiating cells and promoted their proliferation and drug resistance. Drug synergism analysis suggested that AMD3100 treatment undermined the capability of MICs to modulate the bone marrow microenvironment, and thus re-sensitized myeloma to Bortezomib treatments. This work is also the first attempt to virtually visualize in 3D the dynamics of the bone marrow stiffness during myeloma development. In summary, we established a multi-scale model to facilitate the translation of the niche-stiffness centric myeloma model as well as experimental observations to possible clinical applications. We concluded that targeting the biophysical properties of stem cell niches is of high clinical potential since it may re-sensitize tumor initiating cells to chemotherapies and reduce risks of cancer relapse.

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Agent-based modeling: a systematic assessment of use cases and requirements for enhancing pharmaceutical research and development productivity.

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