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      Climate footprint of industry-sponsored in-human clinical trials: life cycle assessments of clinical trials spanning multiple phases and disease areas

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          Abstract

          Objective

          This study aims to calculate the global warming potential, in carbon dioxide (CO 2) equivalent emissions, from all in-scope activities involved in phase 1, 2, 3 and 4 clinical trials spanning multiple disease areas.

          Design

          The study design involved a retrospective analysis of completed clinical trials.

          Setting

          Select set of seven clinical trials conducted between 2018 and 2023 and sponsored by Johnson & Johnson Innovative Medicine: TMC114FD1HTX1002, 77242113PSO2001, 42756493BLC2002, 54767414MMY3012, VAC18193RSV3006, R092670PSY3016 and 28431754DIA4032

          Participants

          While participants and the public were involved in all seven trials, the life cycle assessments (LCAs) were performed as an independent retrospective analysis after the clinical trials were completed. As a retrospective analysis, we leveraged clinical trial documentation and interviews with the sponsor trial staff and trial site staff. None of the participating trial subjects were involved specifically in the LCA analysis, nor was any personal identifying information from the trial subjects collected or shared.

          The underlying clinical trials were performed in accordance with the Declaration of Helsinki and Guidelines for Good Pharmacoepidemiology Practice. All participating investigators were required to obtain full governing board approval for conducting research involving humans. Sponsor approval and continuing review were obtained through the appropriate Institutional Review Board/Ethics Committee (IRB) and Health Authority channels. For academic investigative sites that did not receive authorisation to use the central IRB, full board approval was obtained from their respective governing IRBs, and documentation of approval was submitted to Johnson & Johnson Innovative Medicine, LLC, before the site’s participation and initiation of any trial procedures. All registry participants provided written informed consent and authorisation before participating.

          Primary outcome measure

          Primary outcome measure CO 2 equivalents (CO 2e) for in-scope clinical trial activities calculated according to Intergovernmental Panel on Climate Change 2021 impact assessment methodology.

          Results

          The TMC114FD1HTX1002 phase 1 trial was the smallest trial both in terms of number of patients (39) and sites (1) and had the smallest emissions at 17 648 kgCO 2e. The 54767414MMY3012 phase 3 trial was not the largest trial in terms of number of participating patients (517) but had the largest number of participating sites (129) and had the largest emissions at 3 107 436 kg CO 2e. Across all seven trials analysed, the mean emissions per patient were 3260 kg CO 2e. When the overall trial footprints are broken down by phase, the phase 2 mean per patient was 5722 kg CO 2e and the phase 3 mean per patient emissions were 2499 kg CO 2e. The five largest contributors of greenhouse gas (GHG) emissions were drug product (50% mean), patient travel (10% mean), travel for on-site monitoring visits (10% mean), collection and processing of laboratory samples (9% mean) and sponsor staff commuting (6% mean). Patient travel was the only consistent GHG hotspot across all seven trials, as other hotspots appeared intermittently in some trials but not others based on variations in trial design. Across the multisite phase 2, 3 and 4 trials we analysed, a combination of the observed five largest contributors to GHG emissions were responsible for no less than 79% of GHG emissions for any one trial.

          Conclusions

          Based on our LCAs of seven clinical trials spanning all four phases of development and multiple disease areas, there are five activities that drive no less than 79% of the average clinical trial’s GHG footprint. These are drug product manufacture, packaging, and distribution; patient travel; on-site monitoring visit travel; the collection, transport and processing of laboratory samples; and sponsor staff commuting between their homes and the office. Understanding the activities that drive GHG emissions in clinical trials can both guide trial designers in avoiding or minimising reliance on these activities when designing new trials and guide trial sponsors in taking targeted actions to reduce GHG emissions from these activities where their use cannot be avoided.

          Trial registration number

          TMC114FD1HTX1002 (ClinicalTrials.gov: NCT04208061), 77242113PSO2001 (ClinicalTrials.gov: NCT05364554), 42756493BLC2002 (ClinicalTrials.gov: NCT03473743), 54767414MMY3012 (ClinicalTrials.gov: NCT03277105), VAC18193RSV3006 (ClinicalTrials.gov: NCT05070546), R092670PSY3016 (ClinicalTrials.gov: NCT04072575) and 28431754DIA4032 (ClinicalTrials.gov: NCT04288778).

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          Most cited references26

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          At What Cost to Clinical Trial Enrollment? A Retrospective Study of Patient Travel Burden in Cancer Clinical Trials

          Several barriers to clinical trial participation exist; however, the burden of cost and time associated with travel to visits may contribute to disparities in care. This analysis may inform ways that health care payers and systems can reduce the burden to encourage equitable recruitment and retention in cancer clinical trials. Background. Recent literature suggests that living in a rural setting may be associated with adverse cancer outcomes. This study examines the burden of travel from home to cancer center for clinical trial (CT) enrollees. Materials and Methods. Patients from the University of California San Francisco Clinical Trial Management System database who enrolled in a cancer CT for a breast, genitourinary, or gastrointestinal malignancy between 1993 and 2014 were included. Cancer type, household zip code, race/ethnicity, phase of study, study sponsor, and year of signed consent were exported. Distance traveled from home to center was calculated using a GoogleMaps application programming interface. The relationships of distance with phase of CT, household income, and race/ethnicity were examined. Results. A total of 1,600 patients were enrolled in breast (55.8%), genitourinary (29.4%), or gastrointestinal (14.9%) cancer CTs. The overall median unidirectional distance traveled from home to study site was 25.8 miles (interquartile range [IQR] 11.5–75.3). Of the trial sponsors examined, principal investigator (56.4%), industry (22.2%), cooperative group (11.6%), and National Institutes of Health (NIH; 9.8%), the longest distance traveled was for NIH‐sponsored trials, with a median of 39.4 miles ( p  < .001). Phase I (8.4%) studies had the longest distance traveled, with a median of 41.2 miles (IQR 14.5–101.0 miles; p  = .001). White patients (83%) traveled longer compared with black patients (4.4%), with median distances of 29.9 and 13.9 miles, respectively ( p  < .001). Patients from lower‐income areas ( n  = 799) traveled longer distances compared with patients from higher‐income areas ( n  = 773; 58.3 vs. 17.8 miles, respectively; p  < .001). A multivariable linear model where log10 (distance) was the outcome and adjusting for the exported variables and income revealed that cancer type, year of consent, race/ethnicity, and income were significantly associated with distance traveled. Conclusion. This study found that the burden of travel is highest among patients enrolled in NIH‐sponsored trials, phase I studies, or living in low‐income areas. These data suggest that travel burden for cancer CT participants may be significant. Implications for Practice. This study is one of the first to measure travel distance for patients in cancer clinical trials using a real‐world GoogleMaps calculator. Out‐of‐pocket expenses such as travel are not typically covered by health care payers; therefore, patients may face considerable cost to attend each study visit. Using a single‐center clinical trials enrollment database, this study found that the burden of travel is highest for patients enrolled in National Institutes of Health‐sponsored trials and phase I studies, as well as for patients living in low‐income areas. Results suggest that a significant proportion of patients enrolled in clinical trials face a substantial travel burden.
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            Towards sustainable clinical trials.

            (2007)
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              Carbon cost of pragmatic randomised controlled trials: retrospective analysis of sample of trials

              Objective To calculate the global warming potential, in carbon dioxide (CO2) equivalent emissions, from a sample of pragmatic randomised controlled trials. Design Retrospective analysis. Data source Internal data held by NIHR Evaluation, Trials and Studies Coordinating Centre. Studies included All eligible pragmatic randomised controlled trials funded by the NIHR Health Technology Assessment programme during 2002 and 2003. Main outcome measure CO2 equivalents for trial activities calculated with standard conversion factors. Results 12 pragmatic randomised controlled trials involving more than 4800 participants and a wide range of technologies were included. The average CO2 emission generated by the trials was 78.4 (range 42.1-112.7) tonnes. This is equivalent to that produced in one year by approximately nine people in the United Kingdom. Commuting to work by the trial team generated the most emissions (average 21 (11.5-35.0) tonnes per trial), followed by study centres’ fuel use (18 (9.3-32.2) tonnes per trial), trial team related travel (15 (2.0-29.0) tonnes per trial), and participant related travel (13 (0-46.7) tonnes per trial). Conclusions CO2 emissions from pragmatic randomised controlled trials are generated in areas where steps could be taken to reduce them. A large proportion of the CO2 emissions come from travel related to various aspects of a trial. The results of this research are likely to underestimate the total CO2 emissions associated with the trials studied, because of the sources of information available. Further research is needed to explore the additional CO2 emissions generated by clinical trials, over and above those generated by routine care. The results from this project will feed into NIHR guidelines that will advise researchers on how to reduce CO2 emissions.
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                Author and article information

                Journal
                BMJ Open
                BMJ Open
                bmjopen
                bmjopen
                BMJ Open
                BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )
                2044-6055
                2025
                19 February 2025
                : 15
                : 2
                : e085364
                Affiliations
                [1 ]departmentInnovative Health , Johnson & Johnson Innovative Medicine , Delft, Zuid Holland, The Netherlands
                [2 ]departmentIndustrial Design Engineering , Delft University of Technology , Delft, The Netherlands
                [3 ]Johnson & Johnson Innovative Medicine , Spring House, Pennsylvania, USA
                [4 ]Environmental Resources Management , Ghent, Belgium
                [5 ]departmentProduct Sustainability , Environmental Resources Management , London, UK
                [6 ]Environmental Resources Management , London, UK
                [7 ]ICON plc , Ghent, Belgium
                [8 ]Johnson & Johnson Innovative Medicine , Antwerp, Belgium
                [9 ]Delft University of Technology , Delft, The Netherlands
                Author notes

                Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

                JKL is an employee of Johnson & Johnson Innovative Medicine, LLC, and a member of the faculty at Delft University of Technology. JL is an employee of Johnson & Johnson Innovative Medicine, LLC. RA is an employee of Environmental Resource Management, LLC. MC is an employee of Environmental Resource Management, LLC. TC is an employee of Environmental Resource Management, LLC. HW is an employee of Environmental Resource Management, LLC. AC is an employee of ICON, PLC. WDS is an employee of Johnson & Johnson Innovative Medicine, LLC. JF is a faculty member at Delft University of Technology. KR is an employee of Johnson & Johnson Innovative Medicine, LLC.

                DrJason KeithLaRoche; jlaroche@ 123456its.jnj.com
                Author information
                http://orcid.org/0009-0002-3162-5735
                Article
                bmjopen-2024-085364
                10.1136/bmjopen-2024-085364
                11842993
                39971605
                a8ef7017-98c3-49e8-91e5-7665f3d8aa12
                Copyright © Author(s) (or their employer(s)) 2025. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ Group.

                This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See:  http://creativecommons.org/licenses/by-nc/4.0/.

                History
                : 13 February 2024
                : 21 January 2025
                Funding
                Funded by: Johnson & Johnson Innovative Medicine;
                Categories
                Original Research
                Global Health
                1699
                1506

                Medicine
                clinical trial,neurology,oncology,immunology,diabetes & endocrinology,hiv & aids
                Medicine
                clinical trial, neurology, oncology, immunology, diabetes & endocrinology, hiv & aids

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