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PODCAST

QCast: Data-Driven Dialogue in Drug Development

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.

science life sciences

All Episodes

12:04

Episode 66: What is Clinical Traceability?

QCast: Data-Driven Dialogue in Drug Development ·

2026/10/02

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

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11:36

Episode 65: Clinical Trial Trends Shaping Modern Drug...

QCast: Data-Driven Dialogue in Drug Development ·

2026/09/25

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

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10:13

Episode 64: Tipping Point Analysis in Clinical Trials

QCast: Data-Driven Dialogue in Drug Development ·

2026/09/18

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

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10:26

Episode 63: Audit Trail Review in Clinical Trials

QCast: Data-Driven Dialogue in Drug Development ·

2026/09/11

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

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10:39

Episode 62: Drug Adherence and Persistence

QCast: Data-Driven Dialogue in Drug Development ·

2026/09/04

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

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12:28

Episode 61: The Role of Data Monitoring Committees...

QCast: Data-Driven Dialogue in Drug Development ·

2026/08/28

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 TakeawaysA 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

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11:22

Episode 60: Oncology Phase 1 Trial Design

QCast: Data-Driven Dialogue in Drug Development ·

2026/08/21

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 TakeawaysSafety, exposure, pharmacodynamic information, early activity and longer-term tolerability can all influence the dose and regimen taken forward.Simulation

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10:51

Episode 59: Clinical Data Quality

QCast: Data-Driven Dialogue in Drug Development ·

2026/08/14

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 TakeawaysClinical 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

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10:00

Episode 58: Rescue Studies

QCast: Data-Driven Dialogue in Drug Development ·

2026/08/07

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 TakeawaysA 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

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9:27

Episode 57: Clinical Trial Performance Metrics

QCast: Data-Driven Dialogue in Drug Development ·

2026/07/31

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 TakeawaysSelect a focused set of metrics linked to clear decisions. Measuring more does not automatically improve oversight.Define

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9:55

Episode 56: Bayesian Clinical Trial Design

QCast: Data-Driven Dialogue in Drug Development ·

2026/07/24

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 TakeawaysA Bayesian design combines prior information with current trial data to produce an updated probability distribution.Adaptive decisions depend

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10:27

Episode 55: What is Adaptive Trial Design?

QCast: Data-Driven Dialogue in Drug Development ·

2026/07/17

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 TakeawaysAdaptive changes must be planned in advance, with clear decision rules, timing and analysis methods.Recruitment speed,

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12:09

Episode 54: SAS vs R vs Python in Clinical Trials

QCast: Data-Driven Dialogue in Drug Development ·

2026/07/10

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 TakeawaysSAS, R, and Python can all analyse clinical trial data, but they are not interchangeable.Regulators are concerned with the

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10:52

Episode 53: Decentralised Clinical Trials

QCast: Data-Driven Dialogue in Drug Development ·

2026/07/03

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 TakeawaysDecentralised 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

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9:39

Episode 52: The Global Statistical Test for Multiple...

QCast: Data-Driven Dialogue in Drug Development ·

2026/06/26

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 TakeawaysMultiple endpoints can give a fuller

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10:18

Episode 51: CDASH Standards and Conformance in...

QCast: Data-Driven Dialogue in Drug Development ·

2026/06/19

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 TakeawaysCDASH applies at the point of data collection. It helps teams collect

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10:48

Episode 50: Multi-Omics Application in Personalised...

QCast: Data-Driven Dialogue in Drug Development ·

2026/06/12

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 TakeawaysMulti-omics brings together several types of biological information to help researchers understand disease and treatment response more clearly than a single data layer can

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10:43

Episode 49: BIMO Listings

QCast: Data-Driven Dialogue in Drug Development ·

2026/06/05

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

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9:54

Episode 48: Efficacy Endpoints in Oncology Clinical...

QCast: Data-Driven Dialogue in Drug Development ·

2026/05/29

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 TakeawaysOverall survival remains one of the clearest measures of patient benefit, but it can require longer, larger trials and may be affected by treatments given

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8:39

Episode 47: The Creation of ADaM Datasets for PK...

QCast: Data-Driven Dialogue in Drug Development ·

2026/05/22

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 TakeawaysADPC supports PK concentration data, while ADPP supports derived PK

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