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One carefully selected English reading pack. Thirty focused minutes. Original sources, practical language and one piece of active output.

Latest reading

29 August 2026

C1Human-AI Teaming × Clinical Trials30 min

Why did AI improve trial-screening accuracy without saving time?

Read a randomized Human+AI oncology prescreening study, compare it with TrialMatchAI and CDISC's current AI judging framework, then design separate quality, efficiency, safety and traceability endpoints for one SP AI feature.

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355oncology charts in the randomized evaluation

~5 ppchart-level accuracy gain with Human+AI

5minutes of spoken output

Designed for consistency

Less noise. Better signals.

Source-aware

Official and primary sources establish facts.

Personalised

Priority goes to AI, clinical research, SAS, CDISC and statistical programming.

Active

Every edition ends with retrieval, retelling or a professional speaking task.

August 2026

29 AugHuman-AI trial prescreening: accuracy, efficiency and automation bias↗28 AugStatistical warrant in the age of AI↗27 AugAI automation vs causal validity in target trial emulation↗26 AugWhat should count as evidence that an AI workflow actually works?↗25 AugLLM-assisted statistics: keep inference inside validated methods↗24 AugStatistical programming as research software engineering↗23 AugPrivacy-preserving clinical AI: cloud reasoning, local execution and controlled data boundaries↗22 AugContext engineering for CDISC agents: graph-constrained skills and deterministic validation↗21 AugProcess-DAG agents: bounded ADaM generation, validation gates and retries↗19 AugAI-assisted SDTM mapping: code generation, validation and human approval↗18 AugExecutable SAP metadata: Analysis Concepts, ADaM bindings and ARS↗17 AugFaster clinical development: CROs, real-time signals and SP readiness↗16 AugLegacy SAS modernization: metadata, IR and parity validation↗15 AugAI clinical-trial maturity: from retrospective validation to bounded autonomy↗14 AugSynthetic trial data: false positives, uncertainty and inferential validity↗13 AugClinAgent: tools, skills and validation for clinical statistical programming↗12 AugAI-generated TFLs: standards, traceability and reproducible analysis↗11 AugSynthetic clinical-trial test data: metadata, validation and traceability↗10 AugOperational TrialGPT: local deployment, validation and human escalation↗09 AugOffline policy learning for clinical-development decision agents↗08 AugAgentic AI, real-world data and reproducible trial design↗07 AugLLM-assisted semantics and deterministic TFL QC↗06 AugGenerative AI in REDCap: low-risk MVP and local governance↗05 AugICH M11, structured protocols and metadata-driven automation↗04 AugDigital endpoints, sensor data and reproducible derivations↗03 AugReal-time clinical trials and validated data signals↗02 AugAI-enabled clinical-trial knowledge management↗01 AugLLM-in-the-loop clinical workflow design↗