Advertise on podcast: QCast: Data-Driven Dialogue in Drug Development

AI and machine learning can help research teams make more informed clinical trial design decisions, from assessing protocol feasibility to identifying suitable patient populations. In this QCast episode, Jullia and Tom discuss how predictive modelling, natural language processing, and retrospective analysis can support study planning. Key Takeaways AI can help identify restrictive eligibility criteria, assess patient burden, and inform protocol feasibility before enrolment.Predictive modelling and retrospective analysis can support patient selection and identify treatment response patterns worth investigating in future trials.AI tools require appropriate validation, representative data, and human oversight, with their value assessed against measurable study outcomes. 🔗 Learn More & Get Support: Visit quanticate.com to explore our biometrics services and discover how we can support your next clinical trial. 📝 Episode Notes & Transcript: Find show notes, resources, and a full transcript at quanticate.com/podcast. 🔔 Stay Connected: Subscribe to QCast on Apple Podcasts, Spotify, or your favourite platform to never miss an episode. About Quanticate Founded in 1994, Quanticate is a biometrics-focused CRO with over 30 years' experience delivering expert clinical and post-marketing data services worldwide. Specialising in the collection, management, standardisation, analysis, and reporting of data, we support pharma and biotech companies globally with high-quality solutions for clinical development. We specialise in: Clinical Data Capture & ManagementBiostatistics & Statistical ConsultancyStatistical Programming & PK/PD AnalysisMedical Writing & PharmacovigilanceRegulatory & Submission SupportAI & AutomationPost-Marketing Safety & Real-World DataQuanticate is committed to delivering expertise and solutions that drive the success of clinical development worldwide.

In this episode, Jullia and Tom discuss direct and indirect pathways in observational studies, with a focus on mediation analysis and what it can, and cannot, show. Using an ankylosing spondylitis example, they look at how fatigue, anxiety/depression, and work productivity loss can be mapped as exposure, mediator, and outcome, and why interpretation needs care when the data are observational. Key Takeaways Direct and indirect pathways in this context refer to mediation analysis, not basal ganglia movement-control circuits.Mediation analysis can help examine whether an observed relationship may operate through an intermediate variable, but it does not prove causality on its own.The practical value of pathway analysis depends on clear hypotheses, suitable variable measurement, uncertainty assessment, and careful interpretation. 🔗 Learn More & Get Support: Visit quanticate.com to explore our biometrics services and discover how we can support your next clinical trial. 📝 Episode Notes & Transcript: Find show notes, resources, and a full transcript at quanticate.com/podcast. 🔔 Stay Connected: Subscribe to QCast on Apple Podcasts, Spotify, or your favourite platform to never miss an episode. About Quanticate Founded in 1994, Quanticate is a biometrics-focused CRO with over 30 years' experience delivering expert clinical and post-marketing data services worldwide. Specialising in the collection, management, standardisation, analysis, and reporting of data, we support pharma and biotech companies globally with high-quality solutions for clinical development. We specialise in: Clinical Data Capture & ManagementBiostatistics & Statistical ConsultancyStatistical Programming & PK/PD AnalysisMedical Writing & PharmacovigilanceRegulatory & Submission SupportAI & AutomationPost-Marketing Safety & Real-World DataQuanticate is committed to delivering expertise and solutions that drive the success of clinical development worldwide.

Clinical traceability is about being able to follow evidence from a reported result back to its source and understand the transformations, decisions, and records in between. In this QCast episode, co-hosts Jullia and Tom discuss how traceability can become harder when studies involve multiple systems, CROs, laboratories, and technology providers, and why retaining files alone is not enough. Key Takeaways Strong traceability connects reported results with the underlying data, derivations, programs, and supporting decisions, rather than relying on file retention alone.Outsourced studies can increase traceability complexity because data and responsibilities are distributed across several organisations and systems.A practical review can work in both directions: start with an important result and trace it back to source, then start with a source variable or external data stream and identify which analyses depend on it. 🔗 Learn More & Get Support: Visit quanticate.com to explore our biometrics services and discover how we can support your next clinical trial. 📝 Episode Notes & Transcript: Find show notes, resources, and a full transcript at quanticate.com/podcast. 🔔 Stay Connected: Subscribe to QCast on Apple Podcasts, Spotify, or your favourite platform to never miss an episode. About Quanticate Founded in 1994, Quanticate is a biometrics-focused CRO with over 30 years' experience delivering expert clinical and post-marketing data services worldwide. Specialising in the collection, management, standardisation, analysis, and reporting of data, we support pharma and biotech companies globally with high-quality solutions for clinical development. We specialise in: Clinical Data Capture & ManagementBiostatistics & Statistical ConsultancyStatistical Programming & PK/PD AnalysisMedical Writing & PharmacovigilanceRegulatory & Submission SupportAI & AutomationPost-Marketing Safety & Real-World DataQuanticate is committed to delivering expertise and solutions that drive the success of clinical development worldwide.

Clinical trial trends matter most when they affect how studies are designed, delivered, and overseen. In this QCast episode, co-hosts Jullia and Tom discuss how decentralised models, AI, real-world evidence, adaptive designs, RBQM, outsourcing, and digital trial systems are changing practical decisions for sponsors and CROs. Key Takeaways New trial models can reduce participant burden, but they may add validation, oversight, and data-quality requirements elsewhere.AI and automation work best in clearly defined use cases with human review, documented controls, and clear accountability.Trial design, site readiness, outsourcing, and digital data flows all need to be assessed against the study question, patient population, and operational risk. 🔗 Learn More & Get Support: Visit quanticate.com to explore our biometrics services and discover how we can support your next clinical trial. 📝 Episode Notes & Transcript: Find show notes, resources, and a full transcript at quanticate.com/podcast. 🔔 Stay Connected: Subscribe to QCast on Apple Podcasts, Spotify, or your favourite platform to never miss an episode. About Quanticate Founded in 1994, Quanticate is a biometrics-focused CRO with over 30 years' experience delivering expert clinical and post-marketing data services worldwide. Specialising in the collection, management, standardisation, analysis, and reporting of data, we support pharma and biotech companies globally with high-quality solutions for clinical development. We specialise in: Clinical Data Capture & ManagementBiostatistics & Statistical ConsultancyStatistical Programming & PK/PD AnalysisMedical Writing & PharmacovigilanceRegulatory & Submission SupportAI & AutomationPost-Marketing Safety & Real-World DataQuanticate is committed to delivering expertise and solutions that drive the success of clinical development worldwide.

Tipping point analysis helps trial teams understand how strongly a study conclusion depends on assumptions about missing data. In this QCast episode, co-hosts Jullia and Tom discuss how the method relates to MAR and MNAR, how delta adjustments can identify a tipping point, and why the numerical result still needs clinical interpretation. Key Takeaways Tipping point analysis tests how far assumptions about missing outcomes must change before a predefined trial conclusion changes.The tipping point needs to be interpreted in clinical context, including the endpoint scale, reasons for missingness, and number of participants affected.Continuous, binary, and time-to-event endpoints require different approaches, and prespecification helps keep the analysis aligned with the intended clinical question. 🔗 Learn More & Get Support: Visit quanticate.com to explore our biometrics services and discover how we can support your next clinical trial. 📝 Episode Notes & Transcript: Find show notes, resources, and a full transcript at quanticate.com/podcast. 🔔 Stay Connected: Subscribe to QCast on Apple Podcasts, Spotify, or your favourite platform to never miss an episode. About Quanticate Founded in 1994, Quanticate is a biometrics-focused CRO with over 30 years' experience delivering expert clinical and post-marketing data services worldwide. Specialising in the collection, management, standardisation, analysis, and reporting of data, we support pharma and biotech companies globally with high-quality solutions for clinical development. We specialise in: Clinical Data Capture & ManagementBiostatistics & Statistical ConsultancyStatistical Programming & PK/PD AnalysisMedical Writing & PharmacovigilanceRegulatory & Submission SupportAI & AutomationPost-Marketing Safety & Real-World DataQuanticate is committed to delivering expertise and solutions that drive the success of clinical development worldwide.

Audit trail review can involve far more than checking whether a system records changes. In this QCast episode, co-hosts Jullia and Tom discuss how trial teams can decide what needs review, where risk should shape scope and timing, and why unusual activity needs context before it becomes a finding. Key Takeaways Audit trail review should focus on relevant risks and questions rather than attempting to review every available event.Trial-level and system-level review can have different purposes and owners, so scope and responsibilities need to be clear.A flagged event still needs interpretation against the clinical data and study context before deciding whether action is required. 🔗 Learn More & Get Support: Visit quanticate.com to explore our biometrics services and discover how we can support your next clinical trial. 📝 Episode Notes & Transcript: Find show notes, resources, and a full transcript at quanticate.com/podcast. 🔔 Stay Connected: Subscribe to QCast on Apple Podcasts, Spotify, or your favourite platform to never miss an episode. About Quanticate Founded in 1994, Quanticate is a biometrics-focused CRO with over 30 years' experience delivering expert clinical and post-marketing data services worldwide. Specialising in the collection, management, standardisation, analysis, and reporting of data, we support pharma and biotech companies globally with high-quality solutions for clinical development. We specialise in: Clinical Data Capture & ManagementBiostatistics & Statistical ConsultancyStatistical Programming & PK/PD AnalysisMedical Writing & PharmacovigilanceRegulatory & Submission SupportAI & AutomationPost-Marketing Safety & Real-World DataQuanticate is committed to delivering expertise and solutions that drive the success of clinical development worldwide.

Drug adherence and persistence measures built from claims or EHR databases depend as much on study definitions as recorded treatment events. In this QCast episode, co-hosts Jullia and Tom explain how adherence differs from persistence, what prescribing and dispensing data can and cannot show, and how MPR, PDC, treatment-gap rules and thresholds shape the findings. Key Takeaways Adherence describes how closely medicine use follows the agreed regimen, while persistence measures how long treatment continues before discontinuation.Claims and EHR data provide useful evidence on prescriptions, dispensing and treatment changes, but neither confirms that a patient took the medicine as intended.MPR, PDC and persistence estimates depend on decisions about follow-up, days’ supply, permissible gaps, dose changes, switching and censoring. 🔗 Learn More & Get Support: Visit quanticate.com to explore our biometrics services and discover how we can support your next clinical trial. 📝 Episode Notes & Transcript: Find show notes, resources, and a full transcript at quanticate.com/podcast. 🔔 Stay Connected: Subscribe to QCast on Apple Podcasts, Spotify, or your favourite platform to never miss an episode. About Quanticate Founded in 1994, Quanticate is a biometrics-focused CRO with over 30 years' experience delivering expert clinical and post-marketing data services worldwide. Specialising in the collection, management, standardisation, analysis, and reporting of data, we support pharma and biotech companies globally with high-quality solutions for clinical development. We specialise in: Clinical Data Capture & ManagementBiostatistics & Statistical ConsultancyStatistical Programming & PK/PD AnalysisMedical Writing & PharmacovigilanceRegulatory & Submission SupportAI & AutomationPost-Marketing Safety & Real-World DataQuanticate is committed to delivering expertise and solutions that drive the success of clinical development worldwide.

In this QCast episode, Jullia and Tom discuss the role of data monitoring committees, or DMCs, in clinical trials. They explain how DMCs support participant safety and trial integrity, when independent monitoring may be proportionate, and why confidential interim data needs careful handling. Key Takeaways A DMC provides independent review of accumulating trial data, especially where interim safety, efficacy, futility or benefit-risk decisions may affect study conduct.DMCs are not automatically needed for every trial. Their use should be assessed against the study’s risk profile, design, duration, blinding and planned interim decision points.Clear charters, controlled data access and independent statistical support help protect confidential interim data and reduce the risk of operational bias. 🔗 Learn More & Get Support: Visit quanticate.com to explore our biometrics services and discover how we can support your next clinical trial. 📝 Episode Notes & Transcript: Find show notes, resources, and a full transcript at quanticate.com/podcast. 🔔 Stay Connected: Subscribe to QCast on Apple Podcasts, Spotify, or your favourite platform to never miss an episode. About Quanticate Founded in 1994, Quanticate is a biometrics-focused CRO with over 30 years' experience delivering expert clinical and post-marketing data services worldwide. Specialising in the collection, management, standardisation, analysis, and reporting of data, we support pharma and biotech companies globally with high-quality solutions for clinical development. We specialise in: Clinical Data Capture & ManagementBiostatistics & Statistical ConsultancyStatistical Programming & PK/PD AnalysisMedical Writing & PharmacovigilanceRegulatory & Submission SupportAI & AutomationPost-Marketing Safety & Real-World DataQuanticate is committed to delivering expertise and solutions that drive the success of clinical development worldwide.

In this QCast episode, Jullia and Tom discuss how oncology Phase 1 trial design has moved beyond simply identifying the maximum tolerated dose. They look at dose optimisation, escalation methods, simulation, data readiness, expansion cohorts, biomarkers and site capability, with a focus on how these elements affect real dose decisions. Key Takeaways Safety, exposure, pharmacodynamic information, early activity and longer-term tolerability can all influence the dose and regimen taken forward.Simulation can show how a design behaves when toxicity is delayed, information is incomplete or patients are exposed to doses that are too high or too low.Adverse events, laboratory results, PK and PD data, query resolution, biomarker turnaround and site readiness can all affect whether reviews happen with the evidence expected. 🔗 Learn More & Get Support: Visit quanticate.com to explore our biometrics services and discover how we can support your next clinical trial. 📝 Episode Notes & Transcript: Find show notes, resources, and a full transcript at quanticate.com/podcast. 🔔 Stay Connected: Subscribe to QCast on Apple Podcasts, Spotify, or your favourite platform to never miss an episode. About Quanticate Founded in 1994, Quanticate is a biometrics-focused CRO with over 30 years' experience delivering expert clinical and post-marketing data services worldwide. Specialising in the collection, management, standardisation, analysis, and reporting of data, we support pharma and biotech companies globally with high-quality solutions for clinical development. We specialise in: Clinical Data Capture & ManagementBiostatistics & Statistical ConsultancyStatistical Programming & PK/PD AnalysisMedical Writing & PharmacovigilanceRegulatory & Submission SupportAI & AutomationPost-Marketing Safety & Real-World DataQuanticate is committed to delivering expertise and solutions that drive the success of clinical development worldwide.

In this QCast episode, Jullia and Tom look at how clinical data quality is shaped from study set-up through collection, review and integration. They discuss why clear definitions, well-designed data flows and proportionate quality control matter, particularly when trial data move across multiple systems or vendors. Key Takeaways Clinical data should be judged by whether they are fit for the decisions and analyses the study needs to support, rather than by cleanliness alone.Quality problems often begin upstream. CRF design, data definitions, mappings and study instructions can create issues that later queries cannot fully correct.Review effort should focus on critical data and recurring patterns. Trend review can help identify process problems that isolated record checks may miss. 🔗 Learn More & Get Support: Visit quanticate.com to explore our biometrics services and discover how we can support your next clinical trial. 📝 Episode Notes & Transcript: Find show notes, resources, and a full transcript at quanticate.com/podcast. 🔔 Stay Connected: Subscribe to QCast on Apple Podcasts, Spotify, or your favourite platform to never miss an episode. About Quanticate Founded in 1994, Quanticate is a biometrics-focused CRO with over 30 years' experience delivering expert clinical and post-marketing data services worldwide. Specialising in the collection, management, standardisation, analysis, and reporting of data, we support pharma and biotech companies globally with high-quality solutions for clinical development. We specialise in: Clinical Data Capture & ManagementBiostatistics & Statistical ConsultancyStatistical Programming & PK/PD AnalysisMedical Writing & PharmacovigilanceRegulatory & Submission SupportAI & AutomationPost-Marketing Safety & Real-World DataQuanticate is committed to delivering expertise and solutions that drive the success of clinical development worldwide.

In this QCast episode, Jullia and Tom discuss how sponsors can assess a study in difficulty, decide how to handle existing databases and data, manage handovers, and set realistic expectations for recovery. Key Takeaways A rescue assessment should identify the root cause before corrective work begins.Database rescue does not always require a rebuild.Recovery plans need to reflect what can genuinely be corrected. 🔗 Learn More & Get Support: Visit quanticate.com to explore our biometrics services and discover how we can support your next clinical trial. 📝 Episode Notes & Transcript: Find show notes, resources, and a full transcript at quanticate.com/podcast. 🔔 Stay Connected: Subscribe to QCast on Apple Podcasts, Spotify, or your favourite platform to never miss an episode. About Quanticate Founded in 1994, Quanticate is a biometrics-focused CRO with over 30 years' experience delivering expert clinical and post-marketing data services worldwide. Specialising in the collection, management, standardisation, analysis, and reporting of data, we support pharma and biotech companies globally with high-quality solutions for clinical development. We specialise in: Clinical Data Capture & ManagementBiostatistics & Statistical ConsultancyStatistical Programming & PK/PD AnalysisMedical Writing & PharmacovigilanceRegulatory & Submission SupportAI & AutomationPost-Marketing Safety & Real-World DataQuanticate is committed to delivering expertise and solutions that drive the success of clinical development worldwide.

In this QCast episode, Jullia and Tom examine how clinical trial performance metrics can support better oversight without creating unnecessary reporting burden. They explain the difference between metrics and key performance indicators, why ownership is often shared across sponsors, CROs and sites, and how leading and lagging indicators support different decisions. Key Takeaways Select a focused set of metrics linked to clear decisions. Measuring more does not automatically improve oversight.Define ownership, calculation methods, thresholds and expected responses before reporting begins.Interpret performance in context. A positive-looking number, such as a low query count, may reflect clean data or incomplete review. 🔗 Learn More & Get Support: Visit quanticate.com to explore our biometrics services and discover how we can support your next clinical trial. 📝 Episode Notes & Transcript: Find show notes, resources, and a full transcript at quanticate.com/podcast. 🔔 Stay Connected: Subscribe to QCast on Apple Podcasts, Spotify, or your favourite platform to never miss an episode. About Quanticate Founded in 1994, Quanticate is a biometrics-focused CRO with over 30 years' experience delivering expert clinical and post-marketing data services worldwide. Specialising in the collection, management, standardisation, analysis, and reporting of data, we support pharma and biotech companies globally with high-quality solutions for clinical development. We specialise in: Clinical Data Capture & ManagementBiostatistics & Statistical ConsultancyStatistical Programming & PK/PD AnalysisMedical Writing & PharmacovigilanceRegulatory & Submission SupportAI & AutomationPost-Marketing Safety & Real-World DataQuanticate is committed to delivering expertise and solutions that drive the success of clinical development worldwide.

In this QCast episode, co-hosts Jullia and Tom explain how priors, posterior probabilities and predictive probabilities support clinical decisions. They also discuss external data borrowing, adaptive trial features, simulation, regulatory expectations and the operational work needed to deliver interim decisions without weakening trial credibility. Key Takeaways A Bayesian design combines prior information with current trial data to produce an updated probability distribution.Adaptive decisions depend on timely, review-ready data and predefined governance.Historical borrowing may improve efficiency, but it can also introduce bias when external evidence does not match the current trial. 🔗 Learn More & Get Support: Visit quanticate.com to explore our biometrics services and discover how we can support your next clinical trial. 📝 Episode Notes & Transcript: Find show notes, resources, and a full transcript at quanticate.com/podcast. 🔔 Stay Connected: Subscribe to QCast on Apple Podcasts, Spotify, or your favourite platform to never miss an episode. About Quanticate Founded in 1994, Quanticate is a biometrics-focused CRO with over 30 years' experience delivering expert clinical and post-marketing data services worldwide. Specialising in the collection, management, standardisation, analysis, and reporting of data, we support pharma and biotech companies globally with high-quality solutions for clinical development. We specialise in: Clinical Data Capture & ManagementBiostatistics & Statistical ConsultancyStatistical Programming & PK/PD AnalysisMedical Writing & PharmacovigilanceRegulatory & Submission SupportAI & AutomationPost-Marketing Safety & Real-World DataQuanticate is committed to delivering expertise and solutions that drive the success of clinical development worldwide.

In this QCast episode, Jullia and Tom examine how adaptive trial design allows pre-specified changes to a clinical trial using accumulating interim data. They look at common adaptations, including early stopping, sample size re-estimation and dose selection, while also addressing the statistical, operational and governance controls needed to protect trial integrity. Key Takeaways Adaptive changes must be planned in advance, with clear decision rules, timing and analysis methods.Recruitment speed, endpoint timing and data readiness can determine whether an adaptation is useful in practice.Statistical simulation, operational testing and controlled access to interim results all need to be considered before the first live analysis. 🔗 Learn More & Get Support: Visit quanticate.com to explore our biometrics services and discover how we can support your next clinical trial. 📝 Episode Notes & Transcript: Find show notes, resources, and a full transcript at quanticate.com/podcast. 🔔 Stay Connected: Subscribe to QCast on Apple Podcasts, Spotify, or your favourite platform to never miss an episode. About Quanticate Founded in 1994, Quanticate is a biometrics-focused CRO with over 30 years' experience delivering expert clinical and post-marketing data services worldwide. Specialising in the collection, management, standardisation, analysis, and reporting of data, we support pharma and biotech companies globally with high-quality solutions for clinical development. We specialise in: Clinical Data Capture & ManagementBiostatistics & Statistical ConsultancyStatistical Programming & PK/PD AnalysisMedical Writing & PharmacovigilanceRegulatory & Submission SupportAI & AutomationPost-Marketing Safety & Real-World DataQuanticate is committed to delivering expertise and solutions that drive the success of clinical development worldwide.

In this QCast episode, Jullia and Tom look at SAS vs R vs Python through the lens of clinical trial delivery. Rather than treating the choice as a programming preference, they focus on where each tool tends to fit: SAS for established clinical reporting, R for statistical analysis and visualisation, and Python for automation, integration, and data workflows. Key Takeaways SAS, R, and Python can all analyse clinical trial data, but they are not interchangeable.Regulators are concerned with the integrity of the analysis, not loyalty to a specific tool.Mixed-tool environments can work well when responsibilities are clear. 🔗 Learn More & Get Support: Visit quanticate.com to explore our biometrics services and discover how we can support your next clinical trial. 📝 Episode Notes & Transcript: Find show notes, resources, and a full transcript at quanticate.com/podcast. 🔔 Stay Connected: Subscribe to QCast on Apple Podcasts, Spotify, or your favourite platform to never miss an episode. About Quanticate Founded in 1994, Quanticate is a biometrics-focused CRO with over 30 years' experience delivering expert clinical and post-marketing data services worldwide. Specialising in the collection, management, standardisation, analysis, and reporting of data, we support pharma and biotech companies globally with high-quality solutions for clinical development. We specialise in: Clinical Data Capture & ManagementBiostatistics & Statistical ConsultancyStatistical Programming & PK/PD AnalysisMedical Writing & PharmacovigilanceRegulatory & Submission SupportAI & AutomationPost-Marketing Safety & Real-World DataQuanticate is committed to delivering expertise and solutions that drive the success of clinical development worldwide.