Drug Repurposing: A Systematic Approach to Evaluate Candidate Oral Neuroprotective Interventions for Secondary Progressive Multiple Sclerosis

Objective: To develop and implement an evidence based framework to select, from drugs already licenced, candidate oral neuroprotective drugs to be tested in secondary progressive multiple sclerosis. Design: Systematic review of clinical studies of oral putative neuroprotective therapies in MS and four other neurodegenerative diseases with shared pathological features, followed by systematic review and meta-analyses of the in vivo experimental data for those interventions. We presented summary data to an international multi-disciplinary committee, which assessed each drug in turn using pre-specified criteria including consideration of mechanism of action. Results: We identified a short list of fifty-two candidate interventions. After review of all clinical and pre-clinical evidence we identified ibudilast, riluzole, amiloride, pirfenidone, fluoxetine, oxcarbazepine, and the polyunsaturated fatty-acid class (Linoleic Acid, Lipoic acid; Omega-3 fatty acid, Max EPA oil) as lead candidates for clinical evaluation. Conclusions: We demonstrate a standardised and systematic approach to candidate identification for drug rescue and repurposing trials that can be applied widely to neurodegenerative disorders

Systematic, comprehensive, evidence-based approach to identify neuroprotective interventions for motor neuron disease: using systematic reviews to inform expert consensus

Objectives: Motor neuron disease (MND) is an incurable progressive neurodegenerative disease with limited treatment options. There is a pressing need for innovation in identifying therapies to take to clinical trial. Here, we detail a systematic and structured evidence-based approach to inform consensus decision making to select the first two drugs for evaluation in Motor Neuron Disease-Systematic Multi-arm Adaptive Randomised Trial (MND-SMART: NCT04302870), an adaptive platform trial. We aim to identify and prioritise candidate drugs which have the best available evidence for efficacy, acceptable safety profiles and are feasible for evaluation within the trial protocol. Methods: We conducted a two-stage systematic review to identify potential neuroprotective interventions. First, we reviewed clinical studies in MND, Alzheimer’s disease, Huntington’s disease, Parkinson’s disease and multiple sclerosis, identifying drugs described in at least one MND publication or publications in two or more other diseases. We scored and ranked drugs using a metric evaluating safety, efficacy, study size and study quality. In stage two, we reviewed efficacy of drugs in MND animal models, multicellular eukaryotic models and human induced pluripotent stem cell (iPSC) studies. An expert panel reviewed candidate drugs over two shortlisting rounds and a final selection round, considering the systematic review findings, late breaking evidence, mechanistic plausibility, safety, tolerability and feasibility of evaluation in MND-SMART. Results: From the clinical review, we identified 595 interventions. 66 drugs met our drug/disease logic. Of these, 22 drugs with supportive clinical and preclinical evidence were shortlisted at round 1. Seven drugs proceeded to round 2. The panel reached a consensus to evaluate memantine and trazodone as the first two arms of MND-SMART. Discussion: For future drug selection, we will incorporate automation tools, text-mining and machine learning techniques to the systematic reviews and consider data generated from other domains, including high-throughput phenotypic screening of human iPSCs

Improving our understanding of the in vivo modelling of psychotic disorders: a systematic review and meta-analysis

Psychotic disorders represent a severe category of mental disorders affecting about one percent of the population. Individuals experience a loss or distortion of contact with reality alongside other symptoms, many of which are still not adequately managed using existing treatments. While animal models of these disorders could offer insights into these disorders and potential new treatments, translation of this knowledge has so far been poor in terms of informing clinical trials and practice. The aim of this project was to improve our understanding of these pre-clinical studies and identify potential weaknesses underlying translational failure. I carried out a systematic search of the literature to provide an unbiased summary of publications reporting animal models of schizophrenia and other psychotic disorders. From these publications, data were extracted to quantify aspects of the field including reported quality of studies, study characteristics and behavioural outcome data. The latter of these data were then used to calculate estimates of efficacy using random-effects meta-analysis. Having identified 3847 publications of relevance, including 852 different methods used to induce the model, over 359 different outcomes tested in them and almost 946 different treatments reported to be administered. I show that a large proportion of studies use simple pharmacological interventions to induce their models of these disorders, despite the availability of models using other interventions that are arguably of higher translational relevance. I also show that the reported quality of these studies is low, and only 22% of studies report taking measures to reduce the risk of biases such as randomisation and blinding, which has been shown to affect the reliability of results drawn. Through this work it becomes apparent that the literature is incredibly vast for studies looking at animal models of psychotic disorders and that some of the relevant work potentially overlaps with studies describing other conditions. This means that drawing reliable conclusions from these data is affected by what is made available in the literature, how it is reported and identified in a search and the time that it takes to reach these conclusions. I introduce the idea of using computer-assisted tools to overcome one of these problems in the long term. Translation of results from studies looking at animals modelling uniquely-human psychotic disorders to clinical successes might be improved by better reporting of studies including publishing of all work carried out, labelling of studies more uniformly so that it is identifiable, better reporting of study design including improving on reporting of measures taken to reduce the risk of bias and focusing on models with greater validity to the human condition

Cumulative effects of prenatal-exposure to exogenous chemicals and psychosocial stress on fetal growth: Systematic-review of the human and animal evidence.

BackgroundAdverse effects of prenatal stress or environmental chemical exposures on fetal growth are well described, yet their combined effect remains unclear.ObjectivesTo conduct a systematic review on the combined impact and interaction of prenatal exposure to stress and chemicals on developmental outcomes.MethodsWe used the first three steps of the Navigation Guide systematic review. We wrote a protocol, performed a robust literature search to identify relevant animal and human studies and extracted data on developmental outcomes. For the most common outcome (fetal growth), we evaluated risk of bias, calculated effect sizes for main effects of individual and combined exposures, and performed a random effects meta-analysis of those studies reporting on odds of low birthweight (LBW) by smoking and socioeconomic status (SES).ResultsWe identified 17 human- and 22 animal-studies of combined chemical and stress exposures and fetal growth. Human studies tended to have a lower risk of bias across nine domains. Generally, we found stronger effects for chemicals than stress, and these exposures were associated with reduced fetal growth in the low-stress group and the association was often greater in high stress groups, with limited evidence of effect modification. We found smoking associated with significantly increased odds of LBW, with a greater effect for high stress (low SES; OR 4.75 (2.46-9.16)) compared to low stress (high SES; OR 1.95 (95% CI 1.53-2.48)). Animal studies generally had a high risk of bias with no significant combined effect or effect modification.ConclusionsWe found that despite concern for the combined effects of environmental chemicals and stress, this is still an under-studied topic, though limited available human studies indicate chemical exposures exert stronger effects than stress, and this effect is generally larger in the presence of stress

Dopamine agonists in animal models of Parkinson's disease:A systematic review and meta-analysis

Background: Parkinson's disease (PD) can be a severely disabling condition in spite of therapies currently available. Systematic review and meta-analysis can provide an overview of a field of research and identify potential sources of bias and limits to efficacy. In this study we use these tools to describe the reported efficacy of dopamine agonists in animal models of PD.Methods: Publications were identified by electronic searching of three online databases. Data were extracted for neurobehavioural outcome, for study design and for the reporting of measures to avoid bias. Standardised mean difference meta-analysis was used to provide summary estimates of efficacy, with the effects of study quality and study design explored using stratified meta-analysis.Results: 253 publications reported the use of a dopamine agonist in an animal model of PD; of these 121 reported data suitable for inclusion in meta-analysis. 47 interventions were tested in 601 experiments using 4181 animals. Overall, neurobehavioural outcome was improved by 1.08 standard deviations (SD; 95% Confidence Interval (CI) 0.97-1.19). Reporting of measures to reduce bias was low and publications which reported the blinded assessment of outcome had significantly smaller effect sizes (0.85, 95% CI 0.64 to 1.07) than those which did not (1.18, 95% CI 1.05 to 1.31, p &lt; 0.005).Conclusions: While dopamine agonists do appear to have efficacy in animal models of PD the low prevalence of reporting of measures to avoid bias is of concern. Systematic review of individual interventions may be helpful in the design of future preclinical and clinical trials.</p

Dopamine agonists in animal models of Parkinson's disease:A systematic review and meta-analysis

Background: Parkinson's disease (PD) can be a severely disabling condition in spite of therapies currently available. Systematic review and meta-analysis can provide an overview of a field of research and identify potential sources of bias and limits to efficacy. In this study we use these tools to describe the reported efficacy of dopamine agonists in animal models of PD.Methods: Publications were identified by electronic searching of three online databases. Data were extracted for neurobehavioural outcome, for study design and for the reporting of measures to avoid bias. Standardised mean difference meta-analysis was used to provide summary estimates of efficacy, with the effects of study quality and study design explored using stratified meta-analysis.Results: 253 publications reported the use of a dopamine agonist in an animal model of PD; of these 121 reported data suitable for inclusion in meta-analysis. 47 interventions were tested in 601 experiments using 4181 animals. Overall, neurobehavioural outcome was improved by 1.08 standard deviations (SD; 95% Confidence Interval (CI) 0.97-1.19). Reporting of measures to reduce bias was low and publications which reported the blinded assessment of outcome had significantly smaller effect sizes (0.85, 95% CI 0.64 to 1.07) than those which did not (1.18, 95% CI 1.05 to 1.31, p &lt; 0.005).Conclusions: While dopamine agonists do appear to have efficacy in animal models of PD the low prevalence of reporting of measures to avoid bias is of concern. Systematic review of individual interventions may be helpful in the design of future preclinical and clinical trials.</p