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Statistical Methodology Groups in the Pharmaceutical Industry#.

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Title: Statistical Methodology Groups in the Pharmaceutical Industry#.
Authors: Devenport, Jenny1 (AUTHOR) jenny.devenport@roche.com, Mielke, Tobias2 (AUTHOR), Akacha, Mouna3 (AUTHOR), Rufibach, Kaspar4 (AUTHOR), Ocampo, Alex1 (AUTHOR), Lanius, Vivian5 (AUTHOR), Vandemeulebroecke, Marc6 (AUTHOR), Hougaard, Philip7 (AUTHOR), Collin, Pierre8 (AUTHOR), Wright, David9 (AUTHOR), Hummel, Jurgen10 (AUTHOR), Kunz, Cornelia Ursula11 (AUTHOR), Krams, Mike12 (AUTHOR)
Source: Statistics in Biopharmaceutical Research. Apr-Jun2026, Vol. 18 Issue 2, p194-205. 12p.
Subjects: Statistics methodology, Clinical trials, Pharmaceutical industry, Drug development, Economic efficiency, Quantitative research
Abstract: Research and Development is the largest budget position in the pharmaceutical industry, with clinical trials being a critical, yet costly and time-consuming component to inform decisions. Beyond drug efficacy, probability of success and efficiency are highly dependent on the approaches used for prioritizing, designing, analyzing, and interpreting clinical trials. Deep understanding of statistical methodology and quantitative approaches are therefore essential. Dedicated methodology groups have emerged in mid-size and large pharmaceutical companies and CROs. Their remit is to lead the conception and implementation of innovative quantitative methodologies in order to improve drug development, often by addressing complexities or offering more efficient designs. To achieve this, they collaborate internally and externally (with academics and regulators) to identify common challenges, tear down silos, and invest in methods with the highest impact on efficiency and value to the portfolio. Given the immense financial stakes of drug development—where delays carry massive implications—these groups represent a critical strategic investment. However, to realize this business impact, statistical innovations must be rigorously validated and seamlessly integrated. This manuscript explores the remit and value of dedicated methodology groups, the organizational considerations to address to maximize impact, and the characteristics methodologists need to influence speed, efficiency, and probability of success. [ABSTRACT FROM AUTHOR]
Copyright of Statistics in Biopharmaceutical Research is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Statistical Methodology Groups in the Pharmaceutical Industry<superscript>#</superscript>.
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  Data: <searchLink fieldCode="AR" term="%22Devenport%2C+Jenny%22">Devenport, Jenny</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> jenny.devenport@roche.com</i><br /><searchLink fieldCode="AR" term="%22Mielke%2C+Tobias%22">Mielke, Tobias</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Akacha%2C+Mouna%22">Akacha, Mouna</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Rufibach%2C+Kaspar%22">Rufibach, Kaspar</searchLink><relatesTo>4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Ocampo%2C+Alex%22">Ocampo, Alex</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Lanius%2C+Vivian%22">Lanius, Vivian</searchLink><relatesTo>5</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Vandemeulebroecke%2C+Marc%22">Vandemeulebroecke, Marc</searchLink><relatesTo>6</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Hougaard%2C+Philip%22">Hougaard, Philip</searchLink><relatesTo>7</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Collin%2C+Pierre%22">Collin, Pierre</searchLink><relatesTo>8</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wright%2C+David%22">Wright, David</searchLink><relatesTo>9</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Hummel%2C+Jurgen%22">Hummel, Jurgen</searchLink><relatesTo>10</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Kunz%2C+Cornelia+Ursula%22">Kunz, Cornelia Ursula</searchLink><relatesTo>11</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Krams%2C+Mike%22">Krams, Mike</searchLink><relatesTo>12</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Statistics+in+Biopharmaceutical+Research%22">Statistics in Biopharmaceutical Research</searchLink>. Apr-Jun2026, Vol. 18 Issue 2, p194-205. 12p.
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  Data: <searchLink fieldCode="DE" term="%22Statistics+methodology%22">Statistics methodology</searchLink><br /><searchLink fieldCode="DE" term="%22Clinical+trials%22">Clinical trials</searchLink><br /><searchLink fieldCode="DE" term="%22Pharmaceutical+industry%22">Pharmaceutical industry</searchLink><br /><searchLink fieldCode="DE" term="%22Drug+development%22">Drug development</searchLink><br /><searchLink fieldCode="DE" term="%22Economic+efficiency%22">Economic efficiency</searchLink><br /><searchLink fieldCode="DE" term="%22Quantitative+research%22">Quantitative research</searchLink>
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  Data: Research and Development is the largest budget position in the pharmaceutical industry, with clinical trials being a critical, yet costly and time-consuming component to inform decisions. Beyond drug efficacy, probability of success and efficiency are highly dependent on the approaches used for prioritizing, designing, analyzing, and interpreting clinical trials. Deep understanding of statistical methodology and quantitative approaches are therefore essential. Dedicated methodology groups have emerged in mid-size and large pharmaceutical companies and CROs. Their remit is to lead the conception and implementation of innovative quantitative methodologies in order to improve drug development, often by addressing complexities or offering more efficient designs. To achieve this, they collaborate internally and externally (with academics and regulators) to identify common challenges, tear down silos, and invest in methods with the highest impact on efficiency and value to the portfolio. Given the immense financial stakes of drug development—where delays carry massive implications—these groups represent a critical strategic investment. However, to realize this business impact, statistical innovations must be rigorously validated and seamlessly integrated. This manuscript explores the remit and value of dedicated methodology groups, the organizational considerations to address to maximize impact, and the characteristics methodologists need to influence speed, efficiency, and probability of success. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
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  Data: <i>Copyright of Statistics in Biopharmaceutical Research is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1080/19466315.2026.2656249
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      – Code: eng
        Text: English
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        PageCount: 12
        StartPage: 194
    Subjects:
      – SubjectFull: Statistics methodology
        Type: general
      – SubjectFull: Clinical trials
        Type: general
      – SubjectFull: Pharmaceutical industry
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      – SubjectFull: Drug development
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      – SubjectFull: Economic efficiency
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      – SubjectFull: Quantitative research
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      – TitleFull: Statistical Methodology Groups in the Pharmaceutical Industry#.
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              Text: Apr-Jun2026
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              Y: 2026
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