Claim OwnershipQCast: Data-Driven Dialogue in Drug Development
Subscribed: 1Played: 0
Subscribe
© 2026 QCast: Data-Driven Dialogue in Drug Development
Description
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.
37 Episodes
Reverse
In this QCast episode, Jullia and Tom explore phase 2b in clinical trials and why this stage plays such a decisive role in moving a programme towards phase 3. They explain how phase 2b is typically used to reduce uncertainty around dose, population, endpoints, and treatment effect, and why the study needs to produce data that can support a real development decision rather than just an encouraging signal. Key Takeaways Treat phase 2b as a focused decision study, with design choices centred on ...
In this QCast episode, Jullia and Tom unpack ACR response criteria in rheumatoid arthritis clinical trials and why these endpoints are more operationally demanding than they look on paper. They explain what ACR20, ACR50, and ACR70 measure, how the responder definition depends on consistent joint counts, patient-reported assessments, and timely acute phase reactants, and why a clean-looking binary endpoint can still carry composite-style risks. Key Takeaways Protect the core ACR components at ...
In this QCast episode, Jullia and Tom explore regulatory submissions in clinical trials and why strong submission discipline protects timelines long before any scientific review begins. They discuss what a regulatory submission includes in practice, how early technical validation and portal expectations can derail an otherwise solid package, and where teams most often lose time through version drift, misaligned dependencies, and avoidable publishing and metadata errors. Key Takeaways Treat te...
In this QCast episode, Jullia and Tom unpack therapeutic areas in clinical research and why they matter far beyond a clinical label. They discuss how a therapeutic area shapes trial design assumptions, from endpoint selection and safety oversight to site models, specialist assessments, and the way data moves from collection to review and analysis. Key Takeaways Recognise how therapeutic area choice influences endpoint strategy, safety review cadence, site workflows, and vendor needs from the ...
In this QCast episode, Jullia and Tom break down eCRF design in clinical trials and why it has such an outsized impact on data quality, site workload, and downstream analysis. They clarify what an electronic case report form is meant to do in practice, how it translates protocol requirements into usable data capture, and how to approach validation checks without overburdening sites. Key Takeaways Understand what eCRF design is and how it supports consistent, high-integrity data capture in an ...
In this QCast episode, Jullia and Tom unpack risk-based quality management (RBQM) in clinical data management and why it’s central to protecting participant safety and the reliability of trial results. They clarify what RBQM means in practice, how teams identify critical data and processes, and how KRIs and QTLs can be used to spot emerging issues early and drive proportionate, documented action across functions. Key Takeaways Understand what RBQM is in a clinical data management context, and...
In this QCast episode, Jullia and Tom break down the Investigator’s Brochure (IB) and why it remains a cornerstone of safe, consistent trial conduct. They explain what an IB is, who relies on it, and how it complements the protocol by translating the evolving evidence base into practical guidance on dosing rationale, monitoring, and risk management. Key Takeaways Understand what an Investigator’s Brochure is, who it’s for, and how it supports risk and benefit assessment alongside the pr...
In this QCast episode, Jullia and Tom unpack adaptive randomisation in clinical trials and why teams consider it when fixed allocation feels inefficient or ethically uncomfortable. They explain how response-adaptive randomisation can shift treatment assignment as evidence accumulates, and how patient characteristics can be incorporated through covariate-adjusted response-adaptive randomisation. Key Takeaways Understand what adaptive randomisation is, how it differs from fixed randomisat...
In this QCast episode, Jullia and Tom break down what clinical data management is and why it’s essential to reliable trial decisions. They explain how clinical data management supports patient safety and data integrity from study start-up through to database lock, covering core activities like CRF design, database build, validation checks, query management, reconciliation of external data, and inspection-ready documentation. Key Takeaways Understand what clinical data management covers end to...
In this QCast episode, Jullia and Tom unpack how real world data is analysed to complement clinical trials. They clarify the difference between real world data and real world evidence, explore the main data sources and their trade-offs, and explain how these datasets support trial decisions across feasibility, effectiveness in routine care, and longer-term safety. Key Takeaways Understand the difference between real world data and real world evidence, and why real world analysis is increasing...
In this QCast episode, Jullia and Tom unpack how machine learning is being applied across the pharmaceutical industry. They discuss what machine learning means in a regulated drug development context, where it is already supporting discovery, development, and trial operations, and how teams can use these methods responsibly without undermining scientific or regulatory confidence. Key Takeaways Understand how machine learning differs from traditional statistical approaches, and why it is parti...
In this QCast episode, Jullia and Tom explore medical coding in clinical data management, clarifying how clinical narratives are translated into standardised terminology, why consistent coding underpins safety review and regulatory confidence, and how coding decisions shape analysis-ready datasets across a study’s lifecycle. Key Takeaways Understand how medical coding aligns adverse events, medical history, and medications using controlled dictionaries to support reliable aggregation and inte...
In this QCast episode, Jullia and Tom unpack the proportional odds assumption in ordinal logistic regression, explaining what it means in practice, why it matters for ordinal endpoints in clinical trials, and how to diagnose and handle violations without losing the value of ordered scales. Key Takeaways Understand that proportional odds implies a single treatment effect across all cut points of an ordered endpoint, enabling an efficient summary of benefit.Examine outcome distributions, use fo...
In this QCast episode, Jullia and Tom explore health economics and outcomes research, explaining how outcomes research looks beyond controlled trials to real world care and how HEOR evidence informs pricing, reimbursement, and access decisions. Key Takeaways Anchor HEOR work to a clear decision question around value, pricing, access, or policy.Match methods to the data: define cohorts carefully, respect real world data limits, and invest in strong database infrastructure and quality control.P...
In this QCast episode, Jullia and Tom unpack query management in clinical trials, outlining what queries are, how they move from detection to closure, and how thoughtful design, clear communication, and focused metrics turn them from administrative noise into a practical quality tool that protects data integrity, timelines, and inspection readiness. Key Takeaways Define query management as part of study design, not just an operational clean up activity.Use clear, targeted edit checks and conc...
In this QCast episode, Jullia and Tom explore quality tolerance limits in clinical trials, explaining what they are, how they support risk based quality management, and how to define, monitor and govern them so they genuinely protect participant safety and trial integrity rather than becoming a tick box exercise. Key Takeaways Define QTLs from the risk assessment, link them to truly critical to quality parameters.Set a small number of clear, study level limits, document rationale and calculat...
In this QCast episode, Jullia and Tom unpack data reconciliation in clinical data management — what it is, why it underpins data integrity and safety oversight, and how to plan, run, and document it so analyses reflect the truth across clinical, safety, and vendor systems. Key Takeaways Map streams early, set owners and cadence, lock vendor specifications.Prioritise high-risk data such as safety and endpoints, monitor trends.Standardise units, ranges and identifiers, enforce chang...
In this QCast episode, Jullia and Tom unpack missing data in clinical trials — why it biases effect estimates, how the estimand framework drives prevention and analysis choices, and what good sensitivity work and reporting look like for credible, inspection-ready results. Key Takeaways Define estimands and intercurrent-event strategies, then align follow-up and data collection. Prevent over correct with simpler schedules, remote options, continued follow-up, and early action ...
In this QCast episode, Jullia and Tom demystify data validation in clinical data management — how a lean, risk-based approach safeguards data integrity and supports confident database lock, inspection readiness, and downstream SDTM and ADaM deliverables. Key Takeaways Prioritise a lean Data Validation Plan that targets critical data, tunes top checks, controls changes and captures test evidence.Treat third-party data as first-class by standardising units and timestamps, validating impor...
In this QCast episode, Jullia and Tom unpack real-world evidence in modern drug development — what distinguishes real-world data from the evidence it enables, and how to apply it alongside randomised trials. Key Takeaways Start with the decision, emulate the target trial, and justify methods with clear diagnostics.Make data fitness and governance non-negotiable: provenance, completeness, traceability, privacy, and compliant linkage.Use RWE to complement trials; for external controls, ensure c...
Comments
Download from Google Play
Download from App Store
United States