Technological change and clinical laboratory utilization

Running head: Technology and laboratory utilization.Includes bibliographical references

Modeling the development and dissemination of an emerging medical technology. Vol. 2.

Vol. [2]: Appendices 1 & 2

Benefit Plan Design and Prescription Drug Utilization Among Asthmatics: Do Patient Copayments Matter?

Objective: The ratio of controller to reliever medication use has been proposed as a measure of treatment quality for asthma patients. In this study we examine the effects of plan level mean out-of-pocket asthma medication patient copayments and other features of benefit plan design on the use of controller medications alone, controller and reliever medications (combination therapy), and reliever medications alone. Methods: 1995-2000 MarketScan claims data were used to construct plan-level out-of-pocket copayment and physician/practice prescriber preference variables for asthma medications. Separate multinomial logit models were estimated for patients in fee-for-service (FFS) and non-FFS plans relating benefit plan design features, physician/practice prescribing preferences, patient demographics, patient comorbidities and county-level income variables to patient-level asthma treatment patterns. Results: We find that the controller reliever ratio rose steadily over 1995-2000, along with out-of-pocket payments for asthma medications, which rose more for controllers than for relievers. However, after controlling for other variables, plan level mean out-of-pocket copayments were not found to have a statistically significant influence upon patient-level asthma treatment patterns. On the other hand, physician practice prescribing patterns strongly influenced patient level treatment patterns. Conclusions: There is no strong statistical evidence that higher levels of out-of-pocket copayments for prescription drugs influence asthma treatment patterns. However, physician/practice prescribing preferences influence patient treatment.

Effects of culture media and suspension expansion technologies in mesenchymal stem cell manufacturing - A computational bioprocess and bioeconomics study

Mesenchymal stem cell (MSC) based therapies are promising for a large spectrum of unmet medical needs. Despite this promise, the scaling-up of production of clinical grade MSCs is hindered by the use of planar technologies that require intensive labor and are not enough to meet market demands, as well as due to high product and process variability introduced by the use of xenogeneic materials. This work presents a new bioprocess and bioeconomics model of stem cell expansion to support informed decisions for stem cells process scaling up at reduced annual costs. The intrinsic equations and parameters that capture the cell biological features, according with their source and media used, are embedded in the model. A target number of cells per dose of 140 million and a GMP facility of 400 sq mt with 4 BSCs and 8 incubators will be used as the baseline for expansion of both bone marrow MSCs (BM-MSCs) and adipose stem cells (ASCs) using planar expansion technologies. The current standard medium for MSC culture containing fetal bovine serum (FBS) will be compared with the xeno-free alternative of human platelet lysate (hPL). The use of hPL for both cell sources results in an increase of the number of doses produced and a decrease of the cost of goods (CoG) per dose (Table 1). In order to improve the production capacity, 8 bioreactors with capacity up to 50L were input in the model, using xeno-free plastic microcarriers for cell adhesion and hPL as the culture medium. The model results indicate that the investment in the use of suspension cultures is valuable due to a considerable increase in the production and a decrease of CoG/dose. As the number of doses produced per year increases, the reagent costs dominate relatively to the facility costs (Fig. 1). Sensitivity analysis was performed by varying 11 model variables by +/- 33%. The main factors that influence annual capacity and CoGs are related to harvesting density and yield, growth rates and microcarrier area and concentration (Table 2). These findings may be used to improve the design of expansion methods with fully xeno-free materials and highlight the relevance of the optimization of harvesting and downstream processing protocols. Please click Additional Files below to see the full abstract

An Economic Framework for Evaluating Personalized Medicine

Individual variation accounts for a wide range of medical and economic consequences, from inefficiencies in drug discovery and development to ineffectiveness of drug treatment to drug-induced morbidity and mortality. Addressing these consequences could benefit patients, health care providers and payers, and the pharmaceutical industry. When appropriate markers are known, diagnostic tests allow precise diagnosis and dosing, prediction of disease progression, prediction of treatment response and prediction of adverse drug reactions for individual patients. There may also be substantial savings realized by eliminating costs associated with failed treatment. We developed an analytical framework for analyzing the potential value of using a diagnostic test in clinical practice. Our framework determines the economic consequences of implementing pharmacogenomics in the clinic using a diagnostic test to predict drug response. We offer an empirical test of these ideas: we calculated the cost offset realized by predicting the likelihood of response to an alternative existing treatment using a hypothetical pharmacogenomic test in an asthma population. Because the diagnostic test is hypothetical, our framework is general and could be applied to other indications where diagnostic tests have not been developed. Our results could potentially guide future economic evaluation of new diagnostic tests. Importantly, they may also influence biomarker discovery strategies to ensure consistency between market priorities and the future stream of product introductions

Causal inference in medical records and complementary systems pharmacology for metformin drug repurposing towards dementia.

Metformin, a diabetes drug with anti-aging cellular responses, has complex actions that may alter dementia onset. Mixed results are emerging from prior observational studies. To address this complexity, we deploy a causal inference approach accounting for the competing risk of death in emulated clinical trials using two distinct electronic health record systems. In intention-to-treat analyses, metformin use associates with lower hazard of all-cause mortality and lower cause-specific hazard of dementia onset, after accounting for prolonged survival, relative to sulfonylureas. In parallel systems pharmacology studies, the expression of two AD-related proteins, APOE and SPP1, was suppressed by pharmacologic concentrations of metformin in differentiated human neural cells, relative to a sulfonylurea. Together, our findings suggest that metformin might reduce the risk of dementia in diabetes patients through mechanisms beyond glycemic control, and that SPP1 is a candidate biomarker for metformin's action in the brain

Modeling the development and dissemination of an emerging medical technology. Vol. 1.

Vol. [2]: Appendices 1 & 2

Biomedical innovation : the challenge and the process

HD28 .M414 no.1229-, 81,