Dataset Information

Techno-economic process modelling and Monte Carlo simulation data of uncertainty quantification in field-grown plant-based manufacturing.

ABSTRACT: This data article is related to the research article, "M.J. McNulty, K. Kelada, D. Paul, S. Nandi, and K.A. McDonald, Introducing uncertainty quantification to techno-economic models of manufacturing field-grown plant-made products, Food Bioprod. Process. 128 (2021) 153-165." The raw and analyzed data presented are related to generation, analysis, and optimization of ultra-large-scale field-grown plant-based manufacturing of high-value recombinant protein under uncertainty. The data have been acquired using deterministic techno-economic process model simulation in SuperPro Designer integrated with stochastic Monte Carlo-based simulation in Microsoft Excel using the Crystal Ball plug-in. The purpose of the article is to make techno-economic and associated uncertainty data available to be leveraged and adapted for other research purposes.

SUBMITTER: McNulty MJ

PROVIDER: S-EPMC8405912 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature

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Techno-economic process modelling and Monte Carlo simulation data of uncertainty quantification in field-grown plant-based manufacturing.

McNulty Matthew J MJ Kelada Kirolos K Paul Debashis D Nandi Somen S McDonald Karen A KA

Data in brief 20210821

This data article is related to the research article, <b>"</b>M.J. McNulty, K. Kelada, D. Paul, S. Nandi, and K.A. McDonald, Introducing uncertainty quantification to techno-economic models of manufacturing field-grown plant-made products, Food Bioprod. Process. 128 (2021) 153-165." The raw and analyzed data presented are related to generation, analysis, and optimization of ultra-large-scale field-grown plant-based manufacturing of high-value recombinant protein under uncertainty. The data have ...[more]

PMID: 34485647

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Project description:BackgroundDigital therapeutic care (DTC) programs are unsupervised app-based treatments that provide video exercises and educational material to patients with nonspecific low back pain during episodes of pain and functional disability. German statutory health insurance can reimburse DTC programs since 2019, but evidence on efficacy and reasonable pricing remains scarce. This paper presents a probabilistic sensitivity analysis (PSA) to evaluate the efficacy and cost-utility of a DTC app against treatment as usual (TAU) in Germany.ObjectiveThe aim of this study was to perform a PSA in the form of a Monte Carlo simulation based on the deterministic base case analysis to account for model assumptions and parameter uncertainty. We also intend to explore to what extent the results in this probabilistic analysis differ from the results in the base case analysis and to what extent a shortage of outcome data concerning quality-of-life (QoL) metrics impacts the overall results.MethodsThe PSA builds upon a state-transition Markov chain with a 4-week cycle length over a model time horizon of 3 years from a recently published deterministic cost-utility analysis. A Monte Carlo simulation with 10,000 iterations and a cohort size of 10,000 was employed to evaluate the cost-utility from a societal perspective. Quality-adjusted life years (QALYs) were derived from Veterans RAND 6-Dimension (VR-6D) and Short-Form 6-Dimension (SF-6D) single utility scores. Finally, we also simulated reducing the price for a 3-month app prescription to analyze at which price threshold DTC would result in being the dominant strategy over TAU in Germany.ResultsThe Monte Carlo simulation yielded on average a €135.97 (a currency exchange rate of EUR €1=US $1.069 is applicable) incremental cost and 0.004 incremental QALYs per person and year for the unsupervised DTC app strategy compared to in-person physiotherapy in Germany. The corresponding incremental cost-utility ratio (ICUR) amounts to an additional €34,315.19 per additional QALY. DTC yielded more QALYs in 54.96% of the iterations. DTC dominates TAU in 24.04% of the iterations for QALYs. Reducing the app price in the simulation from currently €239.96 to €164.61 for a 3-month prescription could yield a negative ICUR and thus make DTC the dominant strategy, even though the estimated probability of DTC being more effective than TAU is only 54.96%.ConclusionsDecision-makers should be cautious when considering the reimbursement of DTC apps since no significant treatment effect was found, and the probability of cost-effectiveness remains below 60% even for an infinite willingness-to-pay threshold. More app-based studies involving the utilization of QoL outcome parameters are urgently needed to account for the low and limited precision of the available QoL input parameters, which are crucial to making profound recommendations concerning the cost-utility of novel apps.

Dataset Information

Techno-economic process modelling and Monte Carlo simulation data of uncertainty quantification in field-grown plant-based manufacturing.

Publications

Techno-economic process modelling and Monte Carlo simulation data of uncertainty quantification in field-grown plant-based manufacturing.

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