Using Parallel Coordinates in Optimization of Nano-Particle Drug Delivery.

Nanoparticle drug delivery better targets neoplastic lesions than free drugs and thus has emerged as a safer form of cancer therapy. Nanoparticle design variables are important determinants of efficacy as they influence the drug biodistribution and pharmacokinetics. Previously, we determined optimal designs through mechanistic modeling and optimization. However, the numerical nature of the tumor model and numerous candidate nanoparticle designs hinder hypothesis generation and treatment personalization. In this paper, we utilize the parallel coordinates technique to visualize high-dimensional optimal solutions and extract correlations between nanoparticle design and treatment outcomes. We found that at optimality, two major design variables are dependent, and thus the optimization problem can be reduced. In addition, we obtained an analytical relationship between optimal nanoparticle sizes and optimal distribution, which could facilitate the utilization of tumors models in preclinical studies. Our approach has simplified the results of the previously integrated modeling and optimization framework developed for nanotherapy and enhanced the interpretation and utilization of findings. Integrated mathematical frameworks are increasing in the medical field, and our method can be applied outside nanotherapy to facilitate the clinical translation of computational methods.

Codesigning a systemic discharge intervention for inpatient mental health settings (MINDS): a protocol for integrating realist evaluation and an engineering-based systems approach.

INTRODUCTION: Transition following discharge from mental health hospital is high risk in terms of relapse, readmission and suicide. Discharge planning supports transition and reduces risk. It is a complex activity involving interacting systemic elements. The codesigning a systemic discharge intervention for inpatient mental health settings (MINDS) study aims to improve the process for people being discharged, their carers/supporters and staff who work in mental health services, by understanding, co-designing and evaluating implementation of a systemic approach to discharge planning. METHODS AND ANALYSIS: The MINDS study integrates realist research and an engineering-informed systems approach across three stages. Stage 1 applies realist review and evaluation using a systems approach to develop programme theories of discharge planning. Stage 2 uses an Engineering Better Care framework to codesign a novel systemic discharge intervention, which will be subjected to process and economic evaluation in stage 3. The programme theories and resulting care planning approach will be refined throughout the study ready for a future clinical trial. MINDS is co-led by an expert by experience, with researchers with lived experience co-leading each stage. ETHICS AND DISSEMINATION: MINDS stage 1 has received ethical approval from Yorkshire & The Humber-Bradford Leeds (Research Ethics Committee (22/YH/0122). Findings from MINDS will be disseminated via high-impact journal publications and conference presentations, including those with service user and mental health professional audiences. We will establish routes to engage with public and service user communities and National Health Service professionals including blogs, podcasts and short videos. TRIAL REGISTRATION NUMBER: MINDS is funded by the National Institute of Health Research (NIHR 133013) https://fundingawards.nihr.ac.uk/award/NIHR133013. The realist review protocol is registered on PROSPERO. PROSPERO REGISTRATION NUMBER: CRD42021293255.