Capability
Meta-analysis & data exchange
Fragmented trials, legacy studies, and partner datasets rarely speak the same language. We build synthesis—quantitative where appropriate, qualitative where necessary—that gives BD, regulatory, and access audiences a single, traceable read on what the body of evidence actually shows.
Data rooms, submission modules, and franchise reviews all suffer the same problem: the same body of evidence interpreted differently by each function. We make heterogeneity, missing data, and network assumptions explicit so synthesis strengthens decisions instead of obscuring disagreement behind a single summary figure.
The synthesis challenge
Evidence accumulates across time, geographies, and sponsors: different inclusion criteria, control arms, time points, and missing-data handling. Executives want a headline; regulators and HTA reviewers want traceability; BD teams need speed. Meta-analysis done carelessly—ignoring heterogeneity, mixing populations, or cherry-picking studies—creates liabilities in submissions, investor documents, and litigation discovery. Qualitative synthesis without structure, meanwhile, fails to resolve disagreement when trials point in different directions.
Our approach treats synthesis as both science and communication. Methods must be defensible; narratives must explain what is known, what is uncertain, and what additional data would change the conclusion. That dual lens is what makes synthesis usable in high-stakes settings.
Where we focus
Systematic and structured reviews
We design search strategies, screening workflows, and extraction templates appropriate to the decision at hand—HTA, label support, internal strategy, or public publication. Transparency (PRISMA-style flow, appendices, search strings) is built in, not added later when a reviewer asks.
Meta-analysis and indirect comparisons
We specify effect measures, random-effects versus fixed-effects choices, heterogeneity diagnostics, and sensitivity analyses. For network meta-analyses and ITCs, we document transitivity assumptions and make limitations visible. The output is interpretable for medical leadership, not only for biostatistics.
Data rooms, IPD, and cross-trial mapping
In diligence and partnering, we map endpoints across trials, assess pooling feasibility, and flag inconsistencies between CSR text and tables. Where IPD is available, we evaluate whether patient-level modeling adds value versus aggregate approaches—and what governance is required to use it.
Visualization and executive narrative
Forest plots, league tables, and evidence maps are designed to answer the decision question—not to impress with density. We pair visuals with plain-language summaries suitable for boards and investment committees.
What we deliver
- Protocol-style plans for reviews and meta-analyses with prespecified methods and outcomes.
- Structured evidence tables and endpoint crosswalks across trials and data-room documents.
- Executed meta-analyses or oversight of biostatistical partners with integrated interpretation memos.
- Due diligence summaries separating high-confidence conclusions from inference stretched by sparse data.
- Submission-ready appendices and figure packages where pooled analyses support regulatory or HTA arguments.
- Workshop facilitation when cross-functional teams disagree on what the evidence “says.”
Outcomes you can expect
- Faster alignment on what trials collectively demonstrate—and what they do not.
- Lower risk of embarrassing reversals when experts or agencies probe methods.
- Clearer BD and portfolio decisions grounded in documented synthesis, not slide intuition.
- Reusable evidence infrastructure (endpoints, populations) for future updates and franchises.
How we work
Synthesis is not a black box. We document choices on populations, time points, and effect measures so teams can defend or revise them under scrutiny. For BD contexts, we balance speed with integrity: fast enough for transaction timelines, rigorous enough that medical and legal can sign the summary.
lotor lab integrates clinical judgment with statistical discipline. We collaborate with your biostatisticians and medical writers; we do not replace accountability for methods or authorship where publication or submission is involved.
When teams bring us in
- Asset, licensing, or M&A diligence when CSRs, toplines, and management decks tell different stories.
- Regulatory or HTA filings needing pooled safety, efficacy, or natural-history justification.
- Franchise or therapeutic-area strategy requiring harmonized comparison of in-class assets.
- Post-readout situations where internal debate stalls launch or investment decisions.