The retrospective analysis, our approach to reducing protocol burden, and how to participate in prospective validation.
A retrospective analysis of 275,000 interventional trials from ClinicalTrials.gov found a statistically significant association between estimated temporal design quality and trial outcomes (p = 2.7 × 10−101, Cohen's d = 0.19 all-comers, d = 0.40 oncology). The association replicates across 5 global regions and 10 therapeutic areas. A peer-reviewed methods paper is in preparation for submission to PLOS Medicine (2026).
Trials with sufficient per-patient data density to model individual trajectories succeeded at 58% vs. 27% for those relying on group-level analysis in our retrospective dataset.
Diagnostic Velocity — whether a trial captures how fast things change, not just where they are — ranks as the strongest TRS component in 8 of 10 indications.
TRS is associated with Scientific and Design outcomes but not Operational or Commercial failures — the pattern expected if it captures temporal design adequacy rather than overall sponsor sophistication.
The TRS–outcome association holds across North America, Europe, Asia-Pacific, and multi-regional trials with no regional exceptions in our analysis.
A retrospective association between estimated temporal design quality (TRS) and trial outcomes across 275,000 interventional trials, with effect sizes ranging from d = 0.19 (all indications) to d = 0.40 (oncology). The association replicates across 5 regions, 10 therapeutic areas, and all sponsor types. TRS specifically discriminates Scientific/Design outcomes, not Operational or Commercial failures.
Causation. We have not yet demonstrated that improving a protocol's TRS score changes its outcome. Retrospective association — even a strong one — does not prove that temporal optimization prevents failure. It is possible that higher TRS scores reflect overall sponsor sophistication rather than an independent causal lever. Our prospective Validation Partner program is designed to address this question directly.
A peer-reviewed methods paper for PLOS Medicine (targeted 2026) describing the full methodology, confounding controls, and out-of-sample testing. Expert validation of 100 scored trials through independent reviewers (Kolabtree). Prospective validation partnerships with Phase 2 sponsors implementing TRS recommendations.
A common concern is that optimizing temporal design means adding visits, blood draws, and complexity. Our stepwise triage approach organizes recommendations into three operational tiers, so sponsors implement only what fits their constraints.
Changes that use specimens already being collected, add statistical analyses to existing data, or recompute existing measurements differently. Zero additional blood draws, visits, or procedures.
Adding new assay types to blood or tissue already being collected at scheduled visits. One additional tube at an existing draw, or running an extra panel on an existing biopsy.
New visit timepoints, additional imaging, on-treatment biopsies, or dense early sampling windows. Operationally meaningful but often the highest TRS impact per recommendation.
In our sample portfolio analysis, Tier 1 recommendations alone improved TRS by 2–3 points per trial at near-zero incremental cost. Full stepwise triage with per-recommendation burden classification is available through our NDA full-protocol engagement.
Decentralized clinical trials (DCTs) are reshaping how studies are conducted — but converting a protocol from site-based to hybrid or fully remote changes its temporal architecture in ways that are rarely measured.
When sponsors convert a site-based protocol to a decentralized design, the Schedule of Assessments changes. Site visits become home visits or telehealth check-ins. Specimen collection shifts from on-site phlebotomy to home collection kits with shipping delays. Early mechanistic timepoints — Day 1, Day 3, Day 7 blood draws that capture immune activation or target engagement — are often the first casualties, pushed to later windows or dropped entirely to accommodate remote logistics.
The result is temporal degradation: the decentralized version of the protocol may have a materially lower TRS than the original site-based design. The trial gains operational flexibility and broader patient access, but it may lose the temporal resolution needed to detect the biological signals that determine success or failure.
The solution is not to avoid decentralization — it's to measure and manage the temporal trade-offs intentionally. A DCT Temporal Readiness Assessment scores both versions of the protocol side by side, identifying exactly which temporal capabilities are gained and lost in the transition.
Continuous wearable streams (heart rate variability, activity, temperature, sleep) can provide dense Diagnostic Velocity data that site visits at 4-week intervals never capture. Patient-mediated EHR retrieval provides longitudinal context. Remote ePRO captures real-time symptom trajectories. These capabilities can increase TRS Extensibility and Velocity components.
Early mechanistic blood draws (T1 signaling at Day 1–3), fresh tissue processing (spatial transcriptomics requires <30 min fixation), and on-treatment biopsies all depend on site infrastructure. Losing these timepoints degrades Temporal Alignment and Coverage — the components most strongly associated with trial success in our retrospective analysis.
Smart hybrid designs keep a small number of critical site visits for specimens requiring immediate processing (Day 1 immune activation, on-treatment biopsy) while decentralizing everything else. Home collection kits can capture ctDNA velocity data with acceptable transit times. Wearable integration fills the velocity gap between scheduled draws. The key is knowing which timepoints are site-critical and which can move — TRS identifies this systematically.
The decentralized trials market is projected to reach $18.8B by 2030. As more sponsors adopt hybrid and remote designs, ensuring temporal design integrity during the transition becomes a critical quality gate. TRS provides the framework to make this assessment systematic and quantitative rather than ad hoc.
Answer targeted questions about your study's measurement schedule, specimen types, and sampling density. Takes about 10 minutes. No document upload required.
Suitable for approximately 80% of protocols.
Download our Temporal Design Extractor — a standalone tool that runs entirely on your computer. It parses your .docx protocol, extracts only temporal design elements, and strips all confidential details.
Ideal for complex or multi-arm protocols. Sign up and select "Offline protocol extractor" — we'll send you the download link.
For complex multi-arm protocols, adaptive Bayesian designs, or portfolio-level assessments, we offer full-protocol engagements under mutual NDA. Direct protocol access enables mechanistic cascade mapping, specimen-level operational risk assessment, custom RSM contour visualizations, individual trajectory modeling recommendations, site-level cost modeling, competitive benchmarking, and full stepwise triage with per-recommendation burden classification.
Retrospective analysis shows a strong association. The next step is prospective evidence. We're offering complimentary deep TRS analysis to a limited number of qualifying sponsors willing to participate in our Validation Partner program.
A full-protocol TRS assessment under mutual NDA — including component-level scoring, stepwise triage of optimization recommendations (zero-burden, moderate, and high-impact tiers), indication benchmarking, and cost modeling. Estimated value: $15,000–$25,000 per protocol, provided at no cost to qualifying partners.
Implementation of at least two Tier 1 (zero-burden) or Tier 2 (moderate) recommendations, and agreement to share de-identified outcome data at trial completion. We're particularly interested in Phase 2 oncology and immunology trials with 12–18 month primary endpoints, and neoadjuvant studies with pCR endpoints.
The most common question we hear is: "Has improving a TRS score ever changed a trial outcome?" We believe it has — but belief isn't evidence. This program creates the prospective dataset to answer that question definitively, benefiting both our partners and the broader clinical development community.
1 BIO, Informa Pharma Intelligence, QLS Advisors. Clinical Development Success Rates and Contributing Factors 2011–2020. Phase II success rate: ~30.7%. bio.org
2 Wong CH, Siah KW, Lo AW. Estimation of clinical trial success rates and related parameters. Biostatistics. 2019;20(2):273-286. Oncology overall POS: 3.4%. doi.org
3 Schuhmacher A, et al. Benchmarking R&D success rates of leading pharmaceutical companies. Drug Discovery Today. 2025;30(2):104291. Average LOA: 14.3%. sciencedirect.com
TRS retrospective analysis: Scientari LLC internal analysis of 275,000 interventional trials from ClinicalTrials.gov. Methods paper in preparation for peer-reviewed submission (PLOS Medicine, targeted 2026). The TRS–outcome association is retrospective and correlational. Prospective validation is underway through the Validation Partner program described above.