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Introduction: Oncologists have traditionally administered the maximum tolerated doses of drugs in chemotherapy. However, these toxicity-guided doses may lead to suboptimal efficacy. CURATE.AI is an indication-agnostic, mechanism-independent and efficacy-driven personalised dosing platform that may offer a more optimal solution. While CURATE.AI has already been applied in a variety of clinical settings, there are no prior randomised controlled trials (RCTs) on CURATE.AI-guided chemotherapy dosing for solid tumours. Therefore, we aim to assess the technical and logistical feasibility of a future RCT for CURATE.AI-guided solid tumour chemotherapy dosing. We will also collect exploratory data on efficacy and toxicity, which will inform RCT power calculations.Methods and analysis: This is an open-label, single-arm, two-centre, prospective pilot clinical trial, recruiting adults with metastatic solid tumours and raised baseline tumour marker levels who are planned for palliative-intent, capecitabine-based chemotherapy. As CURATE.AI is a small data platform, it will guide drug dosing for each participant based only on their own tumour marker levels and drug doses as input data. The primary outcome is the proportion of participants in whom CURATE.AI is successfully applied to provide efficacy-driven personalised dosing, as judged based on predefined considerations. Secondary outcomes include the timeliness of dose recommendations, participant and physician adherence to CURATE.AI-recommended doses, and the proportion of clinically significant dose changes. We aim to initially enrol 10 participants from two hospitals in Singapore, perform an interim analysis, and consider either cohort expansion or an RCT. Recruitment began in August 2020. This pilot clinical trial will provide key data for a future RCT of CURATE.AI-guided personalised dosing for precision oncology.Ethics and dissemination: The National Healthcare Group (NHG) Domain Specific Review Board has granted ethical approval for this study (DSRB 2020/00334). We will distribute our findings at scientific conferences and publish them in peer-reviewed journals.Trial registration number: NCT04522284

Chemotherapy-Induced Peripheral Neuropathy (CIPN) is a common dose-limiting side-effect of taxane-based chemotherapy, causing progressive and often irreversible pain/sensitivity in the hands and feet. Prevention/treatments for CIPN are not well-developed and urgently needed. Limb cryocompression during chemotherapy has demonstrated promising early data of preventing/reducing CIPN severity. Currently there are no medical devices available that are dedicated to the specific requirements of CIPN prevention. As part of our ongoing development of a dedicated CIPN-prevention limb cryocompression system, this study documents the design & development of the wearable arm wrap, a central component of the system, from initial concept to a trial-ready prototype. A collaborative and multidisciplinary approach was adopted to address the complex and high-risk nature of this SME (Small Medium Enterprise)-centered medical device design & development process. The complementary collaboration unites multidisciplinary expertise spanning the scope of the project. Alongside the clinical, academic, and design & development expertise, the integration of commercial expertise is imperative to promote the market viability, and ultimate success, of the development. As the global leading experts in scalp cooling specializing in the prevention of chemotherapy-induced alopecia, UK-based SME Paxman Coolers Ltd is optimally positioned to support the commercial and regulatory dimensions. Development and adoption of a novel mixed-methodology (HudPAX) facilitated the integration of evidence-based and user-centered techniques to optimize the design & development approach and ensure integration of all critical design inputs. Alpha prototypes were designed through evidence-based approaches, with data from existing clinical trials utilized to determine the preliminary design inputs, alongside 3D ergonomic data. Investigations utilized computer-aided design, rapid prototyping, additive manufacturing, sketch modeling, and fast ideation. User-based approaches facilitated stakeholder-feedback through expert focus groups, informing further design & development and projecting the design into the next stage, Beta prototyping, for use in large-scale efficacy trials and upscaling manufacturing. This paper demonstrates a novel mixed-methods approach, which promotes cross-sector multidisciplinary collaboration, to address the complex multi-layered challenges posed by an early-stage medical device design & development process.