Clinical trials are the backbone of medical progress, but navigating their design and execution can be complex. Fast Data Science is dedicated to helping researchers by analysing clinical trial protocols through the power of Natural Language Processing (NLP).
We are presenting a selection of software which can be used for clinical trial protocol analysis or clinical trial cost prediction, forecasting, and risk assessment.
Fast Data Science’s Clinical Trial Risk Tool (https://clinical.fastdatascience.com) allows researchers to upload a protocol as a PDF, and it uses an AI model to estimate the risk of the trial ending uninformatively which makes it a go-to clinical trial strategy software for many companies.
The Clinical Trial Risk Tool is free to use for pathologies in an international development context such as HIV and TB, Enteric and diarrheal diseases, Influenza, Neglected tropical diseases, COVID, Malaria, and Polio. For trials in Oncology, Motor neurone disease, Multiple sclerosis, Cystic fibrosis, and other pathologies, it will be available on a subscription basis.
Cost your clinical trial protocol
You can read more on our website about how the Clinical Trial Risk Tool works. The clinical trial protocol software tool was a winner of the Plotly Dash Apps Challenge and has been published and peer-reviewed in Gates Open Research.
This web-based clinical trial software platform facilitates the creation, management, and registration of high-quality protocols, particularly beneficial for researchers in low-resource settings (access through The Global Health Network: https://edctpknowledgehub.tghn.org/protocol-development/septre-protocol-tool/)
This SaaS platform targets the financial aspects of clinical trials, assisting biopharmaceutical companies, CROs, and service providers with budgeting, proposal development, and vendor management (https://strategikonpharma.com/clinical-maestro-2/)
SoftFormance provides tools for planning, managing, and tracking clinical study data, promoting efficiency and transparency throughout the research process (https://www.softformance.com/industries/software-for-clinical-trials/).
Gotrial CLINICA is a cloud-based data platform which integrates complex clinical development datasets such as clinical trial data, regulatory approvals, disease or hospital data - amongst others. Find CLINICA at https://www.gotrial.com/#clinica.
TrialPro is a free clinical trial software that allows you to import PDF protocols and analyses them on a cloud platform. You can create an account and try the tool for free at https://www.trialpro.ai/.
The Clinical Trial Participant Financial Burden Calculator is clinical trial financial management software designed to help potential clinical research participants/ patients better understand and estimate the financial impact and burden of participation. It doesn’t analyse protocols directly like our budgeting and financial modeling software, but you will need to enter the information about the trial manually. Find it at https://trialvalue-burdencalculator.com/.
OpentronsAI uses an interface powered by Generative AI and LLMs, so that scientists can describe experimental protocols in plain language, and OpentronsAI interprets and generates corresponding automated protocol scripts intelligently. Find it at https://opentrons.com/ai.
The Shiny CRT Calculator doesn’t analyse protocols directly but it serves as a tool to calculate power and sample sizes for Cluster Randomised Trials. Find it at https://clusterrcts.shinyapps.io/rshinyapp/.
The best clinical trial protocol analysis software for your research depends on your specific goals. Whether it’s risk assessment, or financial and capacity planning, a dedicated tool can significantly streamline your workflow.
Fast Data Science is committed to expanding our NLP capabilities beyond HIV and TB. Stay tuned for future updates as we strive to empower researchers across a wider range of clinical trials!
Guest post by Safeer Khan, Lecturer at Department of Pharmaceutical Sciences, Government College University, Lahore, Pakistan Clinical trials are the backbone of clinical drug development. They are essential for advancing medicine, testing new therapies, and ensuring patient safety before drugs reach the market. Yet, despite enormous investment, approximately 90% of all clinical trials fail to achieve regulatory approval, according to recent industry studies.[1] Failed trials result in significant financial losses — the average cost of a failed Phase III trial alone can exceed $100 million.
This post originally appeared on Fast Data Science’s blog on LinkedIn. Clinical trials are essential for medical advancement but are not without risk. Delays, budget overruns, and compliance issues can derail the most carefully planned studies. Proactive risk management is the key to ensuring patient safety, maintaining regulatory compliance, and achieving successful trial outcomes. In this article we’ll explore the key risks in clinical trials, how AI-powered tools like the Clinical Trial Risk Tool can help mitigate these risks, and practical strategies for ongoing risk monitoring.
This post originally appeared on Fast Data Science’s blog on LinkedIn. Discover how the Clinical Trial Risk Tool helps optimise clinical trial workflows with accurate risk and cost analysis. Save time and reduce costs. Why Workflow Efficiency Matters in Clinical Trials Running a clinical trial is a complex and expensive process. Delays, unexpected costs, and inefficiencies can waste time and money, affecting trial outcomes and patient care. As trials become more complicated, workflow management is more important than ever.
