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Comparison · Analytics

DoseFinding vs RBesT

A side-by-side editorial comparison of DoseFinding and RBesT — release velocity, themes, recent moves, and the top alternatives to consider.

Shared themes:clinical-trials

DoseFinding vs RBesT: at a glance

FeatureDoseFindingRBesT
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesdose-response, mcp-mod, clinical-trials, model-averagingbayesian-statistics, clinical-trials, stan, r-language
Last editorial update1h ago2h ago
WebsiteVisit →Visit →

What is DoseFinding?

New stewardship at openpharma, then two releases adding the methods MCP-Mod was missing

DoseFinding implements MCP-Mod and related dose-response methodology for clinical trial design and analysis. In 2024 it changed hands — Marius Thomas took over as maintainer, Novartis was recorded as copyright holder and funder, and the package moved to the openpharma GitHub organisation with roxygen documentation and a proper NEWS file. The two releases since have added substantive methodology: model averaging for dose-response fitting in 1.3-1, and conditional and predictive power for interim analyses in 1.4-1.

Read the full DoseFinding trajectory →

What is RBesT?

RBesT is teaching its Bayesian decision rules to answer two-sided questions.

RBesT builds meta-analytic-predictive priors — the machinery for borrowing historical control data into a new trial — and evaluates the operating characteristics of decisions made with them. The stable line has spent several releases on effective sample size: ESS for normal mixtures via a new `family` argument, boundary corrections when no responses or no non-responses are observed, and stabilised ELIR computations. The 1.9-0 release candidate extends the normal, binomial and Poisson outcome functions to two-sided decisions.

Read the full RBesT trajectory →

DoseFinding vs RBesT: editorial side-by-side

D
DoseFinding
ANALYTICS
0.0

New stewardship at openpharma, then two releases adding the methods MCP-Mod was missing

◆ Current state

DoseFinding implements MCP-Mod and related dose-response methodology for clinical trial design and analysis. In 2024 it changed hands — Marius Thomas took over as maintainer, Novartis was recorded as copyright holder and funder, and the package moved to the openpharma GitHub organisation with roxygen documentation and a proper NEWS file. The two releases since have added substantive methodology: model averaging for dose-response fitting in 1.3-1, and conditional and predictive power for interim analyses in 1.4-1.

◆ Where it's heading

The pattern before the handover was maintenance — R-devel compliance, a bug fix, a link. After it, each release carries a named methodological addition with an acknowledged contributor, plus documentation to match: a longitudinal analysis vignette shipped alongside the interim power work. Housekeeping continues underneath, mostly clearing deprecated ggplot2 interfaces, aes_string in one release and qplot in the next.

◆ Prediction

Given the last two releases each added one method with a supporting vignette, expect the next to follow the same shape. Both additions so far extend the package beyond fixed dose-response fitting, so adaptive and interim methodology is the more likely direction.

R
RBesT
ANALYTICS
0.0

RBesT is teaching its Bayesian decision rules to answer two-sided questions.

◆ Current state

RBesT builds meta-analytic-predictive priors — the machinery for borrowing historical control data into a new trial — and evaluates the operating characteristics of decisions made with them. The stable line has spent several releases on effective sample size: ESS for normal mixtures via a new `family` argument, boundary corrections when no responses or no non-responses are observed, and stabilised ELIR computations. The 1.9-0 release candidate extends the normal, binomial and Poisson outcome functions to two-sided decisions.

◆ Where it's heading

Two currents run through the changelog. One is ESS hardening — nearly every release since 1.7-4 fixes another edge case where the ELIR calculation aborted or returned something unstable, which is what happens when a quantity used to justify prior strength to regulators gets scrutinised. The other is Stan and brms integration debt: array syntax updates, a minimum Stan version bump, truncated prior generation for `mixstanvar`, deterministic EM. The RC's contributor list shows a second active maintainer, and the work is broader than any recent stable release.

◆ Prediction

The release candidate covers all three outcome families and has already absorbed a round of review comments, so the next step is most likely the 1.9-0 CRAN release itself rather than further feature work.

Alternatives to DoseFinding and RBesT

Other Analytics products tracked by Sparkpulse, ranked by recent ship velocity. Each card links to a full editorial trajectory and lets you pivot into a head-to-head comparison with either DoseFinding or RBesT.

See all DoseFinding alternatives → · See all RBesT alternatives →

Recent activity from DoseFinding and RBesT

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 5mo agoRBesTTwo-sided decisions across normal, binomial and Poisson outcomes
  2. 1y agoDoseFindingConditional and predictive power for interim analyses
  3. 1y agoRBesTJSON read and write for mixture objects
  4. 1y agoDoseFindingModel averaging arrives for dose-response fitting
  5. 1y agoRBesTess() fixed inside apply functions
  6. 1y agoRBesTESS for normal mixtures in the exponential family
  7. 1y agoRBesTTruncated mixture priors for brms, plus faster Stan models
  8. 1y agoDoseFindingPackage moves to openpharma under new maintainership
  9. 2y agoRBesTStan array syntax update and CRAN system requirements
  10. 2y agoDoseFindingCompliance update for R-devel
  11. 3y agoDoseFindingpowMCTBinCount bug fix

Frequently asked questions

What is the difference between DoseFinding and RBesT?

Both compete on the same themes — clinical-trials — within Analytics. DoseFinding and RBesT are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.

Is DoseFinding better than RBesT?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. DoseFinding and RBesT are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.

What are the best alternatives to DoseFinding?

Top DoseFinding alternatives in Analytics are ranked by recent ship velocity. Browse the "DoseFinding alternatives" section above for the current picks, or visit /alternatives/dosefinding for the full list with editorial commentary on each.

What are the best alternatives to RBesT?

Top RBesT alternatives in Analytics are ranked by recent ship velocity. Browse the "RBesT alternatives" section above for the current picks, or visit /alternatives/rbest for the full list with editorial commentary on each.