Claim OwnershipQCast: Data-Driven Dialogue in Drug Development
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© 2025 QCast: Data-Driven Dialogue in Drug Development
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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.
22 Episodes
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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...
In this QCast episode, Jullia and Tom explore the dose expansion phase of phase one oncology trials — the critical bridge between dose finding and proof of concept. They discuss how expansion cohorts confirm safety, explore early efficacy signals, and refine dose and schedule decisions, along with best practices for design, governance, and regulatory alignment that set the stage for a successful phase two. Key Takeaways Treat the dose expansion phase as a structured bridge between dose ...
In this QCast episode, Jullia and Tom unpack Statistical Analysis Plans (SAPs) — the blueprints that define how clinical trial data are turned into evidence. They explore what a SAP includes, how it links to the protocol and estimand framework, and the controls that keep analyses credible, reproducible, and inspection-ready. Key Takeaways Treat the SAP as the bridge between protocol intent and statistical execution. Anchor all analyses to the estimand framework to maint...
In this QCast episode, Jullia and Tom demystify case report form annotation in clinical trials. They explain what an annotated CRF is, why it is central to traceability and compliance, and how teams use CDASH at collection and SDTM at tabulation to keep mappings clean. Key Takeaways Treat the annotated CRF as the contract between collection and analysis to ensure end-to-end traceability.Start from CDASH templates and map cleanly to SDTM; extend standards only with clear rationale.Lock units a...
In this QCast episode, Jullia and Tom break down how the R programming language is being used for clinical trial data analysis. They explore its role across the trial lifecycle, from planning and cleaning through efficacy, safety, and reporting. Key Takeaways Use the language for simulations, cleaning, modelling, safety, and reporting across the trial lifecycle.Build “reporting datasets” to simplify creation of inspection-ready tables and figures.Validate processes with pinned versions, docum...
In this QCast episode, Jullia and Tom demystify estimands and show how a clear question, defined up front, sharpens trial design, data capture, and analysis. They unpack the four elements, explain practical strategies for handling intercurrent events, and discuss picking summary measures that clinicians and payers can interpret. Key Takeaways Define the estimand early and in plain language; align objectives, CRFs, and the analysis plan to the same question.Match intercurrent event strat...
In this QCast episode, Jullia and Tom explain how AI and automation make clinical data work smoother from smarter screening and electronic consent to streaming device data, auto-summarising notes, targeted monitoring, and faster reports. They outline the basics for linking core trial systems, clarify what regulators expect on validation and audit trails, and share a simple first-year plan with quick wins and common traps to avoid. Key Takeaways Start small with a high-value workflow, define s...
In this QCast episode, Jullia and Tom explore the rise of virtual clinical trials—what they are, when they work best, and how to design them without compromising safety or data quality. They cover the regulatory expectations across the US, EU, and UK, walk through a participant’s journey in a decentralised model, explain how oversight, technology, and logistics must align for success, highlight pitfalls that commonly derail virtual studies, and share the practical safeguards that make them wo...
In this QCast episode, Jullia and Tom uncover how Data and Safety Monitoring Boards (DSMBs) keep trials safe and on track—what they are, when you need one, and how to avoid data pitfalls at interim looks. They unpack the DSMB charter versus the Data Safety Monitoring Plan, translate stopping boundaries into plain English, and share practical tactics for clean, blinded packages that enable confident decisions. Key Takeaways Proportional oversight keeps risk in check; higher-risk or adapt...
In this QCast episode, Jullia and Tom break down randomisation in clinical trials—why it matters, how different methods work, and what safeguards keep allocations fair and consistent across sites. They cover simple, block, and stratified randomisation, touch on unequal allocation and adaptive designs, and share a practical case study from a 5-arm trial. Key Takeaways Randomisation reduces bias, supports blinding, and strengthens trial validity.Simple, block, and stratified methods suit ...
In this QCast episode, join co-hosts Jullia and Tom as they unpack the database lock process in clinical trials. You’ll get a clear explanation of what a lock is, why it matters, and the difference between soft and hard locks. They’ll walk through the planning steps that keep the final weeks on track, the habits that reduce last-minute issues, and the cross-functional coordination needed to reach lock on time. Key Takeaways Database lock is a formal milestone where the trial dataset becomes c...
In this QCast episode, join co-hosts Jullia and Tom as they break down Phase 1 clinical trial designs. You’ll learn exactly what happens in single and multiple ascending-dose stages, discover modern dose-escalation methods, and find out how food-effect, interaction and bioequivalence studies fit in. They’ll also share practical strategies for combining objectives, using adaptive protocols and cutting timelines without sacrificing data quality. Key Takeaways Phase 1 is more than a basic ...
In this QCast episode, join co-hosts Jullia and Tom as they explore the ALCOA++ Principles for clinical trial data integrity. You'll get clear definitions of the five original ALCOA pillars, the new additions, and learn how to put them into practice across paper, electronic, and hybrid systems. Key Takeaways ALCOA++ is your data backbone, defining ten attributes that keep every record reliable, auditable, and long-lasting.The original ALCOA pillars ensure every entry shows who did what, when,...
In This QCast episode, join co-hosts Jullia and Tom as they unpack CDISC standards in clinical research, exploring the core content models from PRM to SEND, the exchange formats like ODM-XML and Define-XML, and how to streamline your trials with faster regulatory approvals, lower costs, and analytics-ready datasets. Key Takeaways CDISC standards are a unified set of content and exchange models for collecting, structuring, and submitting clinical trial data.Their core concepts include end-to-e...
In this QCast episode, join co-hosts Jullia and Tom as they unpack the Bayesian Optimal Interval, or BOIN, design for early-phase oncology studies. You'll hear how BOIN blends Bayesian reasoning with simple decision rules, why regulators now call it 'fit for purpose,' and how sponsors are using it to speed up dose-finding while keeping patient safety front and centre. Key Takeaways BOIN design is a model-assisted Bayesian dose-escalation method with pre-defined escalation, de-escalation and s...
In this QCast episode, join Jullia and Tom as they unpack Complex Innovative Trial Designs (CIDs), exploring how adaptive and Bayesian methods – from response-adaptive randomisation to platform protocols – are transforming clinical research by boosting efficiency, personalisation, and speed. Key Takeaways What makes a trial 'complex and innovative': adaptive rules, Bayesian borrowing, and seamless master protocols.Four CID categories: traditional adaptive, biomarker-guided, Bayesian borrowing...
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