Introducing S′ as a Potency-Efficacy Index for High‑Throughput Drug Viability Screening; Reframing Drug Response as Net Regulatory Balance

Introducing S′ as a Potency-Efficacy Index for High‑Throughput Drug Viability Screening; Reframing Drug Response as Net Regulatory Balance | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Method Article Introducing S′ as a Potency-Efficacy Index for High‑Throughput Drug Viability Screening; Reframing Drug Response as Net Regulatory Balance Matthew E. Zamora, Michael R. Muchow, Ishani Ray, Nathan D. McKinley-Pace, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9559070/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The bidirectional response of signaling networks when direct inhibition and feedback-driven activation coexist is not captured by conventional metrics such as IC₅₀, EC₅₀, and AUC used in high-throughput screening (HTS). The direction of response - growth inhibition or growth stimulation - is critical in some scenarios, including anticancer agents HTS. We reformulated the transduction term of the Black–Leff operational model to capture not only the magnitude of the effect but also its directionality (inhibitory, neutral, or disinhibitory). As a result, the index S’ is a unitless metric of directionality, potency, and efficacy, for coherent comparison across compounds with descending (inhibition) or ascending (disinhibition/stimulation) dose–response curves. The cohort-level extension, ΔS’, quantifies genotype-specific differences in drug response and reveals mutation-dependent vulnerabilities, including candidate synthetic-lethal interactions in PTEN-, TP53-, and NF1-altered cancer backgrounds. By capturing both inhibition and disinhibition, S′ and ΔS′ provide a unified operational framework for identifying feedback-driven reversal in response directionality, ranking compounds more precisely, and mapping pathway dependencies across heterogeneous cancer cell populations. The S′ and ΔS′ metrics can be directly estimated from existing HTS datasets for more accurate therapeutic prioritization and drug repurposing comparing to traditional concentration–response metrics. Cancer Biology Computational Biology operational pharmacology Black–Leff model potency–efficacy index (S′) differential sensitivity inhibition disinhibition drug repurposing cancer pharmacology Full Text Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9559070","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Method Article","associatedPublications":[],"authors":[{"id":631392519,"identity":"5c23563c-f72a-4c22-ba6e-45a615be2a78","order_by":0,"name":"Matthew E. 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The direction of response - growth inhibition or growth stimulation - is critical in some scenarios, including anticancer agents HTS.\u003c/p\u003e \u003cp\u003eWe reformulated the transduction term of the Black\u0026ndash;Leff operational model to capture not only the magnitude of the effect but also its directionality (inhibitory, neutral, or disinhibitory). As a result, the index S\u0026rsquo; is a unitless metric of directionality, potency, and efficacy, for coherent comparison across compounds with descending (inhibition) or ascending (disinhibition/stimulation) dose\u0026ndash;response curves. The cohort-level extension, ΔS\u0026rsquo;, quantifies genotype-specific differences in drug response and reveals mutation-dependent vulnerabilities, including candidate synthetic-lethal interactions in PTEN-, TP53-, and NF1-altered cancer backgrounds.\u003c/p\u003e \u003cp\u003eBy capturing both inhibition and disinhibition, S\u0026prime; and ΔS\u0026prime; provide a unified operational framework for identifying feedback-driven reversal in response directionality, ranking compounds more precisely, and mapping pathway dependencies across heterogeneous cancer cell populations. The S\u0026prime; and ΔS\u0026prime; metrics can be directly estimated from existing HTS datasets for more accurate therapeutic prioritization and drug repurposing comparing to traditional concentration\u0026ndash;response metrics.\u003c/p\u003e","manuscriptTitle":"Introducing S′ as a Potency-Efficacy Index for High‑Throughput Drug Viability Screening; Reframing Drug Response as Net Regulatory Balance","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-30 02:58:22","doi":"10.21203/rs.3.rs-9559070/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f9277949-8518-4393-a357-5d39391f0ac8","owner":[],"postedDate":"April 30th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":67201721,"name":"Cancer Biology"},{"id":67201722,"name":"Computational Biology"}],"tags":[],"updatedAt":"2026-04-30T02:58:22+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-30 02:58:22","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9559070","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9559070","identity":"rs-9559070","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}