Evidence map›Paper›PMID 42380698›Full record

ArticleTherapeutic innovation & regulatory science2026

Implementing Project Optimus in Oncology Dosage Optimization: Where are We Now?

Revathi Ananthakrishnan, Patrick Mitchell, Dong Xi, Gu Mi, Gina D'Angelo, Haijun Ma, Yujun Wu, Philip He

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Article in Therapeutic innovation & regulatory science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Revathi AnanthakrishnanBristol-Myers Squibb (BMS), Princeton, NJ, USA.ORCID http://orcid.org/0000-0003-1730-3756
Patrick MitchellAstraZeneca (AZ), Gaithersburg, MD, USA.
Dong XiGilead, Foster City, CA, USA.
Gu MiSanofi, Cambridge, MA, USA.ORCID http://orcid.org/0000-0001-8778-954X
Gina D'AngeloAstraZeneca (AZ), Gaithersburg, MD, USA.ORCID http://orcid.org/0000-0002-5327-086X
Haijun MaRevolution Medicines, Redwood City, CA, USA.
Yujun WuOncolytics Biotech Inc, San Diego, USA.
Philip HeDaiichi Sankyo, Inc, 211 Mt Airy Rd, Basking Ridge, NJ, 07920, USA. Philipyihe2018@gmail.com.ORCID http://orcid.org/0000-0001-6804-1501

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Determining the optimal dosage of oncology drugs is a critical component of drug development, as many anticancer agents are associated with high toxicity. With the emergence of targeted therapies and immunotherapies, the conventional concept that "more is better" may not apply, as higher doses do not necessarily yield greater efficacy and may compromise tolerability. In response to repeated post-approval dosage modifications, the U.S. Food and Drug Administration (FDA) launched Project Optimus in 2021 to promote data-driven, patient-centered dosage optimization. Despite the release of the finalized FDA Guidance for Industry on Oncology Dosage Optimization in 2024, sponsors continue to face challenges in translating these recommendations into practice, due to the complexity in the development process of oncology drugs and the limitations of early-phase trials. To gain insight into current practices and challenges, the DahShu Innovative Designs Scientific Working Group (IDSWG) conducted an industry-wide survey among oncology statisticians in biopharmaceutical companies. The survey revealed a shift away from reliance on the maximum tolerated dose toward integrated strategies balancing efficacy, safety, pharmacokinetics, and patient experience. This paper summarizes the findings from that survey and offers practical recommendations emphasizing cross-functional collaboration between statisticians and other functional members in early phase trials, adoption of innovative trial designs, and proactive regulatory engagement regarding dosage optimization strategies in clinical development.

Indexed as

Antineoplastic AgentsNeoplasmsDose-Response Relationship, DrugDrug DevelopmentHumansMaximum Tolerated DoseUnited StatesUnited States Food and Drug AdministrationAntineoplastic AgentsDosage optimizationEfficacyPK/PDPRORandomized trial comparing dosesTotality of dataToxicity

Identifiers

PMID42380698

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.