Episode 69: SDTM Mapping Automation Tool

A clinical development plan should connect the evidence a programme needs with its studies, decision points, regulatory interactions and resources. In this QCast episode, co-hosts Jullia and Tom examine how a well-structured CDP turns clinical development strategy into an executable programme, while allowing teams to respond to emerging data without losing scientific discipline.Key TakeawaysEach study should address a defined gap or support a clear programme decision.Predefined measures, thresholds and actions help teams assess results consistently while retaining credible alternative paths.Regulatory, safety, operational and resourcing assumptions should be reviewed after major data readouts, authority interactions and programme decisions.🔗 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 QuanticateFounded 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 design decisions can have consequences across the protocol, analysis and delivery of a study. In this QCast episode, co-hosts Jullia and Tom examine how a clear research question should guide the study population, endpoints, comparator and statistical approach.Key TakeawaysA specific treatment objective helps ensure that the design, endpoint and comparator address the clinical decision the study needs to support.Sample size and analysis assumptions should be tested while the protocol can still be adjusted, then revisited when the endpoint, schedule, or participant burden changes.Recruitment potential, site capability, and the demands placed on participants can directly affect adherence, missing data, and dropout.🔗 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 QuanticateFounded 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 examine how SDTM mapping automation tools use approved rules and metadata to generate mapping specifications and SAS code, and where AI can assist with unfamiliar variables.Key TakeawaysApproved mappings can be reused across studies and updated when protocol requirements change, reducing repetitive programming.ML can suggest mappings for unfamiliar variables, but recommendations still require review against the source data and study requirements.Passing automated validation checks doesn't necessarily mean a dataset accurately represents the collected data. Independent QC remains essential.🔗 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 QuanticateFounded 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.

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 TakeawaysAI 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 QuanticateFounded 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 TakeawaysDirect 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 QuanticateFounded 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 TakeawaysStrong 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 QuanticateFounded 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 TakeawaysNew 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 QuanticateFounded 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 TakeawaysTipping 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 QuanticateFounded 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 TakeawaysAudit 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 QuanticateFounded 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 TakeawaysAdherence 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 QuanticateFounded 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.