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Published by Quanticate
QCast by Quanticate is the podcast for biotech, pharma, and life science leaders looking to deepen their understanding of biometrics and modern drug development. Join co-hosts Tom and Jullia as they explore methodologies, case studies, regulatory shifts, and industry trends shaping the future of clinical research. Where biometric expertise meets data-driven dialogue, QCast delivers practical insights and thought leadership to inform your next breakthrough.
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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 & Management Biostatistics & Statistical Consultancy Statistical Programming & PK/PD Analysis Medical Writing & Pharmacovigilance Regulatory & Submission Support AI & Automation Post-Marketing Safety & Real-World Data Quanticate 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 & Management Biostatistics & Statistical Consultancy Statistical Programming & PK/PD Analysis Medical Writing & Pharmacovigilance Regulatory & Submission Support AI & Automation Post-Marketing Safety & Real-World Data Quanticate 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 & Management Biostatistics & Statistical Consultancy Statistical Programming & PK/PD Analysis Medical Writing & Pharmacovigilance Regulatory & Submission Support AI & Automation Post-Marketing Safety & Real-World Data Quanticate 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 & Management Biostatistics & Statistical Consultancy Statistical Programming & PK/PD Analysis Medical Writing & Pharmacovigilance Regulatory & Submission Support AI & Automation Post-Marketing Safety & Real-World Data Quanticate 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 & Management Biostatistics & Statistical Consultancy Statistical Programming & PK/PD Analysis Medical Writing & Pharmacovigilance Regulatory & Submission Support AI & Automation Post-Marketing Safety & Real-World Data Quanticate 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 & Management Biostatistics & Statistical Consultancy Statistical Programming & PK/PD Analysis Medical Writing & Pharmacovigilance Regulatory & Submission Support AI & Automation Post-Marketing Safety & Real-World Data Quanticate 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 & Management Biostatistics & Statistical Consultancy Statistical Programming & PK/PD Analysis Medical Writing & Pharmacovigilance Regulatory & Submission Support AI & Automation Post-Marketing Safety & Real-World Data Quanticate 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 & Management Biostatistics & Statistical Consultancy Statistical Programming & PK/PD Analysis Medical Writing & Pharmacovigilance Regulatory & Submission Support AI & Automation Post-Marketing Safety & Real-World Data Quanticate 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 & Management Biostatistics & Statistical Consultancy Statistical Programming & PK/PD Analysis Medical Writing & Pharmacovigilance Regulatory & Submission Support AI & Automation Post-Marketing Safety & Real-World Data Quanticate 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 & Management Biostatistics & Statistical Consultancy Statistical Programming & PK/PD Analysis Medical Writing & Pharmacovigilance Regulatory & Submission Support AI & Automation Post-Marketing Safety & Real-World Data Quanticate is committed to delivering expertise and solutions that drive the success of clinical development worldwide.
In this QCast episode, Jullia and Tom discuss decentralised clinical trials and what they mean for clinical development teams in practice. The episode looks at decentralisation as a spectrum of remote, local, digital, and site-based activity, rather than a move to fully virtual trials. Key Takeaways Decentralised clinical trials work best when remote and local activities are selected deliberately. Data management is central to decentralised trial delivery. Investigator oversight still applies when trial activities move away from the site. 🔗 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 & Management Biostatistics & Statistical Consultancy Statistical Programming & PK/PD Analysis Medical Writing & Pharmacovigilance Regulatory & Submission Support AI & Automation Post-Marketing Safety & Real-World Data Quanticate is committed to delivering expertise and solutions that drive the success of clinical development worldwide.
In this QCast episode, Jullia and Tom discuss the Global Statistical Test for multiple endpoints analysis and why it can be useful when a clinical trial needs to assess more than one outcome at the same time. They cover the problem of testing endpoints separately, how GST supports an overall assessment of treatment effect, and why endpoint choice, correlation, missing data, and clinical interpretation need to be planned before the analysis is run. Key Takeaways Multiple endpoints can give a fuller view of treatment effect, but testing them separately increases the chance of false positive findings. GST can provide one overall assessment across a related set of endpoints, while still requiring endpoint-level review to understand what is driving the result. GST works best when endpoints answer a shared clinical question, move in a consistent expected direction, and are supported by clear analysis planning. 🔗 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 & Management Biostatistics & Statistical Consultancy Statistical Programming & PK/PD Analysis Medical Writing & Pharmacovigilance Regulatory & Submission Support AI & Automation Post-Marketing Safety & Real-World Data Quanticate is committed to delivering expertise and solutions that drive the success of clinical development worldwide.
In this QCast episode, Jullia and Tom discuss CDASH standards and conformance in clinical data management, with a focus on where CDASH sits in the clinical data flow and why it matters before data reaches SDTM. The episode looks at CRF and eCRF design, naming conventions, metadata, controlled terminology, ePRO and eSource data, and the practical problems that can appear when collection standards are applied too late. Key Takeaways CDASH applies at the point of data collection. It helps teams collect clinical trial data consistently before it is mapped into SDTM for review and submission. Conformance depends on more than including the right fields. Naming conventions, metadata and traceability all affect whether data can move cleanly from capture through to SDTM. Early alignment reduces avoidable rework. Bringing data management and programming into CRF design can help prevent repeated queries, unclear site responses and manual review issues later. 🔗 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 & Management Biostatistics & Statistical Consultancy Statistical Programming & PK/PD Analysis Medical Writing & Pharmacovigilance Regulatory & Submission Support AI & Automation Post-Marketing Safety & Real-World Data Quanticate is committed to delivering expertise and solutions that drive the success of clinical development worldwide.
In this QCast episode, Jullia and Tom discuss multi-omics and its application in personalised medicine studies. The episode explains how genomic, transcriptomic, proteomic, metabolomic and other biological data layers can be analysed together to better understand disease, treatment response and patient subgroups. Key Takeaways Multi-omics brings together several types of biological information to help researchers understand disease and treatment response more clearly than a single data layer can provide. Multi-omics can support biomarker discovery, patient stratification and exploratory analysis, but findings need clear evidence before they can guide treatment, diagnosis or prevention. Sample timing, visit labels, subject identifiers, protocol deviations and data quality checks all influence whether multi-omics data can be linked meaningfully to clinical 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 & Management Biostatistics & Statistical Consultancy Statistical Programming & PK/PD Analysis Medical Writing & Pharmacovigilance Regulatory & Submission Support AI & Automation Post-Marketing Safety & Real-World Data Quanticate is committed to delivering expertise and solutions that drive the success of clinical development worldwide.
In this QCast episode, Jullia and Tom discuss BIMO listings and their role in FDA inspection readiness. They explain how Bioresearch Monitoring looks at clinical trial conduct, participant protection, data credibility, and the records that support regulatory submissions. The episode also covers common misconceptions, including the idea that BIMO is only a site-level concern, and shows how sponsors can use inspection findings to strengthen oversight before issues become harder to resolve. Key Takeaways BIMO oversight looks beyond final datasets. It considers how data was collected, reviewed, documented, and supported by source records. BIMO listings can highlight patterns around protocol deviations, informed consent, adverse event reporting, data management, and submission readiness. Good preparation depends on timely data entry, clear query handling, documented decisions, version control, and records that can be retrieved and explained. 🔗 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 & Management Biostatistics & Statistical Consultancy Statistical Programming & PK/PD Analysis Medical Writing & Pharmacovigilance Regulatory & Submission Support AI & Automation Post-Marketing Safety & Real-World Data Quanticate is committed to delivering expertise and solutions that drive the success of clinical development worldwide.
In this QCast episode, Jullia and Tom discuss efficacy endpoints in oncology clinical trials and why endpoint choice shapes how treatment benefit is assessed. They look at overall survival, progression-free survival, objective response rate, disease-free survival, event-free survival, symptom endpoints, and quality-of-life measures. Key Takeaways Overall survival remains one of the clearest measures of patient benefit, but it can require longer, larger trials and may be affected by treatments given after the study therapy. Progression-free survival and objective response rate can show treatment activity earlier, but they answer different questions from overall survival. Scan timing, missed assessments, censoring decisions, symptom questionnaires, and quality-of-life completion rates can all affect endpoint 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 & Management Biostatistics & Statistical Consultancy Statistical Programming & PK/PD Analysis Medical Writing & Pharmacovigilance Regulatory & Submission Support AI & Automation Post-Marketing Safety & Real-World Data Quanticate is committed to delivering expertise and solutions that drive the success of clinical development worldwide.
In this QCast episode, Jullia and Tom discuss how ADaM datasets are created for pharmacokinetic, or PK, analysis. They look at the role of ADPC for concentration data and ADPP for derived PK parameters, including how these datasets relate to SDTM PC and PP. The episode also covers why timing, dosing information, analysis values, flags and study-specific rules matter when preparing PK data for reporting and review. Key Takeaways ADPC supports PK concentration data, while ADPP supports derived PK parameters such as Cmax, Tmax, AUC and half-life. Both datasets help turn PK data into an analysis-ready structure. PK results depend on the relationship between dosing and sample collection. Planned and actual time points, relative time variables and pre-dose samples all need careful handling. Analysis values, flags and criteria variables help show which records were analysed, which were excluded and why. This makes PK outputs easier to review and reproduce. 🔗 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 & Management Biostatistics & Statistical Consultancy Statistical Programming & PK/PD Analysis Medical Writing & Pharmacovigilance Regulatory & Submission Support AI & Automation Post-Marketing Safety & Real-World Data Quanticate is committed to delivering expertise and solutions that drive the success of clinical development worldwide.
In this QCast episode, Jullia and Tom discuss clinical data review as an active part of study oversight, rather than a late-stage clean-up exercise. They explore how timely, connected review supports subject safety, data quality, medical review and confident decision-making, especially as trial data now comes from EDC, ePRO, eCOA, labs, imaging, biomarkers, wearables and other sources. Key Takeaways Good review helps teams spot patterns, missing context and signals that may affect trial conduct or subject safety before issues become embedded. A lab result, adverse event or dosing change becomes more useful when it can be reviewed alongside related data at the right point in the study. Dashboards, alerts and automation can help focus attention, but teams still need clear ownership, escalation routes, traceability and risk-based priorities. 🔗 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 & Management Biostatistics & Statistical Consultancy Statistical Programming & PK/PD Analysis Medical Writing & Pharmacovigilance Regulatory & Submission Support AI & Automation Post-Marketing Safety & Real-World Data Quanticate is committed to delivering expertise and solutions that drive the success of clinical development worldwide.
In this QCast episode, Jullia and Tom discuss clinical trial management systems and their role in keeping clinical studies under control. They explain how CTMS differs from EDC, why operational visibility matters across recruitment, monitoring, site activity and documentation, and how a well-used system can support risk-based oversight, audit trails and better decision-making across sponsors, CROs and sites. Key Takeaways A CTMS gives study teams a central view of milestones, site activation, monitoring activity, recruitment, documents, payments and follow-up actions. When CTMS connects with systems such as EDC, eTMF, safety platforms and finance tools, teams can reduce duplicate entry and work from a more reliable operational picture. The right CTMS should reflect real trial workflows, support current guidance expectations around oversight, and help teams act earlier when risks or delays appear. 🔗 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 & Management Biostatistics & Statistical Consultancy Statistical Programming & PK/PD Analysis Medical Writing & Pharmacovigilance Regulatory & Submission Support AI & Automation Post-Marketing Safety & Real-World Data Quanticate is committed to delivering expertise and solutions that drive the success of clinical development worldwide.
In this QCast episode, co-hosts Jullia and Tom explore clinical trial simulation and how it supports better study design decisions before a trial begins. They explain how simulation uses statistical and mathematical models to test plausible study scenarios, rather than relying on a single fixed assumption. Key Takeaways Simulation helps teams see how a study design may behave under different assumptions around treatment effect, variability, dropout, recruitment, or safety. The right model depends on the question, whether that is dose selection, endpoint choice, interim planning, or operational feasibility. Simulation is most useful when scenarios reflect clinical and operational reality, with clear assumptions, verification, and communication. 🔗 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 & Management Biostatistics & Statistical Consultancy Statistical Programming & PK/PD Analysis Medical Writing & Pharmacovigilance Regulatory & Submission Support AI & Automation Post-Marketing Safety & Real-World Data Quanticate is committed to delivering expertise and solutions that drive the success of clinical development worldwide.
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