Prescribing the Right Agent for Depression in Adults (PRADA): a Double-blind, Randomised Controlled Trial Using a Web-based Multi-modal Clinical Decision Support System and Genetic Information to Personalise Antidepressant Treatment in Diverse Clinical Settings Across the Globe

Overview

Depression is a common mental health problem affecting almost 300 million people worldwide. Antidepressants are recommended as one of the first line treatments for people with moderate-to-severe symptoms of depression. In our recent trial, PETRUSHKA, on the acute treatment of depression, we demonstrated that the PETRUSHKA Tool, an evidence-based shared decision support system to personalise antidepressant treatment, in comparison with usual care reduced by almost 40% the number of participants stopping their antidepressant early, also improving their depression and anxiety symptoms. To identify the best treatment for each individual, the PETRUSHKA Tool used clinical and demographic predictors. Pilot data show that genetic information can aid stratification of people experiencing depression and better target their treatment. Genetic data can be collected using low-cost DNA-sequencing technology in diverse clinical settings and low-resource environments. Hence, we hypothesised that individual-level pharmacogenomic information can further personalise antidepressant treatment. In this project called PRADA ("Prescribing the Right Agent for Depression in Adults"), we will develop and test in a global trial across Ethiopia, Pakistan and the UK, an evidence-based multimodal web-tool to help participants and clinicians choose the best pharmacological treatment for depression jointly, based on participant preferences and their individual clinical, demographic, cultural, and also genetic profile (PRADA Tool). We will compare the new tool with the PETRUSHKA Tool in a blind fashion, measuring adherence to antidepressant treatment, clinical response and quality of life over a 12-month follow-up.

Major depressive disorder (MDD) is characterised by substantial heterogeneity in treatment response and tolerability. Although antidepressants are recommended as first-line treatment for moderate-to-severe depression, in routine care the selection of a specific antidepressant remains largely empirical. As a result, many patients discontinue treatment prematurely due to lack of efficacy, or the presence of intolerable side effects. This limits the overall effectiveness of pharmacological interventions. Our previous trial PETRUSHKA, an international, multicentre randomised controlled trial (RCT), addressed this challenge by developing and evaluating a web-based clinical decision-support system that integrated clinical and demographic predictors with participant preferences to personalise antidepressant selection and treatment. We demonstrated that antidepressant treatment can be optimised for individuals by using socio-demographic and clinical predictors, and patient preferences. Recent studies have shown the beneficial role of pharmacogenomics to improve antidepressant response and reduce adverse effects in patients with MDD. In 2023, the Clinical Pharmacogenetics Implementation Consortium provided updated guidelines for choice and dosage of SSRIs and SNRIs based on genotypes at CYP2D6, CYP2C19, and CYP2B6 variants. Notably, pharmacogenetic variants have been studied extensively across global populations, in which they have similar influences but different frequencies between ancestry groups. Polygenic scores (PGS), while not diagnostic per se, can also contribute useful information about risk. Advanced but economical DNA sequencing technologies now exist, suitable for use in low resource environments, returning results in as little as 48 hours. Hence, pharmacogenomic variants and PGS can provide timely individual-level information, especially about adverse effects and genetic vulnerability for depression, that can be used to further personalise treatments and empower patients in the management of their symptoms . Moreover, genetic data could help identify patient subgroups with specific molecular characteristics associated with clinical features, that can also inform animal model studies and ultimately support drug discovery in neuroscience. The PRADA trial builds directly on the PETRUSHKA framework by evaluating an enhanced, multimodal clinical decision-support system that incorporates also pharmacogenomic information (the PRADA Tool), compared to a system based only on clinical and demographic factors and patient preferences (the PETRUSHKA Tool). The trial is aimed to determine whether the PRADA tool can further improve personalisation of antidepressant treatment, improving its acceptability and clinical outcomes. Both the PRADA Tool and the PETRUSHKA Tool employ bespoke algorithms in the back end to identify the best antidepressant for each individual participant. The algorithms: (a) are based on prediction models which use a combination of advanced analytics (statistics) and machine learning methods (artificial intelligence); (b) use a dataset which is a combination of real-world data (QResearch: https://www.qresearch.org/) from over 1 million primary care patients with depression in England and Wales, and individual participant data from approximately 40,000 participants recruited in randomised controlled trials; (c) incorporate preferences from participants, and clinicians (especially about adverse events); (d) generate a ranked list of personalised treatment recommendations that will inform the clinical discussion between clinicians and participant, and the final treatment decision. The difference between the PRADA Tool and the PETRUSHKA Tool is that the PRADA Tool will also use pharmacogenomic information and more personalised preferences about efficacy (i.e., specific clusters of symptoms participants want to target) and tolerability (i.e., specific adverse events participants would like to avoid). To maintain the double-blind nature of the trial, all participants (irrespectively of whether they are randomised to the PRADA Tool, or the PETRUSHKA Tool) and clinicians will see and interact with an identical interface, available as the same web-based application and accessible from any computer, smartphone, or tablet. This single interface for all participants will be used to collect participants' preferences and present the list of recommended treatments to participants and clinicians. All participants will be asked the same questions in the tool frontend and all participants will have their genetic data analysed. The pharmacogenetic data and symptom prioritisation will be used in selecting the antidepressant only for participants randomised to the PRADA Tool and will not be used for the participants randomised to the comparator tool. The pharmacogenetic data will not be disclosed to participants or clinicians via the tool or at any other stage of the trial. Additional blood samples will be collected at screening from all participants and these will be processed and used for downstream exploratory research in ethically approved studies, or transferred to an HTA licenced biobank. Participants from the UK and Pakistan will also be offered the opportunity to take part in a sub-study at week 8 focussing on the delivery Polygeneic Scores (PGS). The aim of the Polygeneic Score delivery component of the trial is to compare two methods of delivering genetic test results about depression and evaluate whether the addition of genetic counselling, alongside the report and genetic information provided, impacts participants' empowerment. Using a factorial design, participants in both arms will be individually randomised to receive either: (a) a written report on their customised PGS for depression, accompanied by tailored material explaining how to interpret this information; or (b) the same written report and tailored material, plus a one-to-one session (delivered remotely or face to face) with a genetic counsellor to discuss and explain the results. Participants in the UK only will also have the opportunity to take part in two other sub-studies; a microbiome sample collection and sensor data collection. For the microbiome study, participants will be asked if they wish to provide stool samples for gut microbiome profiling and the completion of questionnaires related to diet and digestion three times during the PRADA trial ( screening to week 24). At the end of the sub-study, they will receive a digital report of their microbiome data. Particpants in the UK may opt to take part in a sensor data collection using the mindLAMP mental health platform. The aim of this sub-study is to explore whether passively-collected smartphone data can be used to derive longitudinal behavioural markers relevant to depression, including mobility, routine regularity, and activity levels. The sub-study will last 8 weeks from baseline and particpants will be asked to complete a short daily questionnaire via the mindLAMP app. Following completion of data collection, the participant will receive a digital personalised summary report describing behavioural patterns observed during the study period.