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Drug Development in Tissue-Agnostic Indications.

ABSTRACT: A better understanding of cancer biology has led to the development of targeted therapies specifically designed to modulate an altered molecular pathway in the cancer cells or their microenvironment. Despite the identification of molecular targets across cancer types, most of targeted therapies were developed per cancer type. In this ancestral paradigm, randomization was the gold-standard approach for market access. Randomization of large patient populations was feasible for drugs developed in common cancer types but more challenging in rare cancer types. The traditional paradigm of drug development in oncology was further challenged by the ever-expanding molecular segmentation of cancer with ever-smaller subgroups of patients who might benefit from specific targeted therapies or immunotherapies and the identification of molecular alterations against which drugs may be effective across cancer types. In this novel drug development paradigm, novel ways of evaluating the efficacy of drugs are highly needed in these small patient populations. One approach is to use each patient as his/her own control by comparing the efficacy of a drug to the efficacy of prior treatments received. This approach allows to overcome patient heterogeneity, especially in a tissue-agnostic drug development paradigm.

SUBMITTER: du Rusquec P

PROVIDER: S-EPMC8199632 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundWith the large amount of pharmacological and biological knowledge available in literature, finding novel drug indications for existing drugs using in silico approaches has become increasingly feasible. Typical literature-based approaches generate new hypotheses in the form of protein-protein interactions networks by means of linking concepts based on their cooccurrences within abstracts. However, this kind of approaches tends to generate too many hypotheses, and identifying new drug indications from large networks can be a time-consuming process.MethodologyIn this work, we developed a method that acquires the necessary facts from literature and knowledge bases, and identifies new drug indications through automated reasoning. This is achieved by encoding the molecular effects caused by drug-target interactions and links to various diseases and drug mechanism as domain knowledge in AnsProlog, a declarative language that is useful for automated reasoning, including reasoning with incomplete information. Unlike other literature-based approaches, our approach is more fine-grained, especially in identifying indirect relationships for drug indications.Conclusion/significanceTo evaluate the capability of our approach in inferring novel drug indications, we applied our method to 943 drugs from DrugBank and asked if any of these drugs have potential anti-cancer activities based on information on their targets and molecular interaction types alone. A total of 507 drugs were found to have the potential to be used for cancer treatments. Among the potential anti-cancer drugs, 67 out of 81 drugs (a recall of 82.7%) are indeed known cancer drugs. In addition, 144 out of 289 drugs (a recall of 49.8%) are non-cancer drugs that are currently tested in clinical trials for cancer treatments. These results suggest that our method is able to infer drug indications (original or alternative) based on their molecular targets and interactions alone and has the potential to discover novel drug indications for existing drugs.

Project description:BackgroundTissue-agnostic drug development provides a paradigm shift in precision medicine and requires innovative trial designs. However, outcome selection for such trials can prove challenging. The objectives of this review were to: (i) Identify and map core outcome sets (COS), across 11 immune-mediated inflammatory diseases (IMIDs) in order to facilitate the selection of relevant outcomes across the conditions for innovative trials of tissue-agnostic drug therapies. (ii) Compare outcomes or endpoints recommended by the US Food and Drug Administration (FDA) and European Medicines Agency (EMA) to identify and highlight similarities and differences.MethodsThe Core Outcome Measures in Effectiveness Trials (COMET), International Consortium for Health Outcomes Measurement (ICHOM), FDA and EMA databases were searched from inception to 28th December 2019. Two reviewers independently screened titles and abstracts of retrieved entries and conducted the subsequent full text screening. Hand searching of the reference lists and citation searching of the selected publications was conducted. The methodological quality of the included peer-reviewed articles was independently assessed by the reviewers based on the items of the COS-Standards for Development recommendations (COS-STAD) checklist. Core outcomes from the included publications were extracted and mapped across studies and conditions. Regulatory guidance from FDA and EMA, where available for clinical trials for the IMIDs, were obtained from their databases and recommendations on outcomes to measure directly compared.ResultsForty-four COS publications were included in the final analysis. Outcomes such as disease activity, pain, fatigue, quality of life, physical function, work limitation/productivity, steroid use and biomarkers were recommended across majority of the conditions. There were significant similarities and differences in FDA and EMA recommendations. The only instance where either regulatory body directly referenced a COS was for jSLE-both referenced the Paediatric Rheumatology International Trials Organization (PRINTO) COS.ConclusionsThe findings from this systematic review provide valuable information to inform outcome selection in tissue-agnostic trials for IMIDs. There is a need for increased collaboration between regulators and COS developers and inclusion of regulators as key stakeholders in COS development to enhance the quality of COS.Trial registrationNot registered.

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Drug Development in Tissue-Agnostic Indications.

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