Background
The healthcare sector contributes substantially to environmental pollution, affecting ecosystems and public health. Circular economy (CE) strategies offer potential solutions, but existing frameworks provide limited guidance for healthcare, overlooking factors such as infection control, decontamination, and staff workload.

Methods
We developed the Circular Healthcare Flows visual, a taxonomy of CE strategies for medical devices, using observations in sterilization departments, recycling facilities, and manufacturing plants; 21 expert interviews; and a systematic review of 1104 studies (68 full-text reviews). Additional stakeholder feedback validated and refined the taxonomy.

Findings
The taxonomy identifies 13 CE strategies—refuse, replace, rethink, reduce, reuse, maintain, repair, refurbish, remanufacture, repurpose, recycle, renew, and recover—and organizes them in a healthcare-specific framework. Iterative feedback ensured that the taxonomy is clear, practically applicable, and addresses sector-specific regulatory, clinical, and operational constraints.

Interpretation
The Circular Healthcare Flows visual provides a practical tool to standardize terminology and guide the implementation of CE strategies in healthcare. By offering conceptual structure and actionable guidance, it supports informed decision-making, facilitates collaboration among stakeholders, and encourages consistent application of circular strategies across the sector.

Funding
IJzenbrandt was partially funded by Erasmus University Rotterdam and the Health and Technology Convergence Alliance of TU Delft, Erasmus MC, and Erasmus University Rotterdam. Hoveling was funded through the DiCE project (EU grant agreement no. 101060184). Opinions expressed are those of the authors and do not necessarily reflect those of the EU or REA.

Objective
This study aims to calculate the global warming potential, in carbon dioxide (CO2) 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 CO2 equivalents (CO2e) 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 kgCO2e. 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 CO2e. Across all seven trials analysed, the mean emissions per patient were 3260 kg CO2e. When the overall trial footprints are broken down by phase, the phase 2 mean per patient was 5722 kg CO2e and the phase 3 mean per patient emissions were 2499 kg CO2e. 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.

To design products and systems in harmony with nature, we can look to nature’s designs.
For inspiration from mentors: Define the problem biologically.
Find mentor organisms and their strategies, either through direct observation or online/literature sources. Translate biological strategies into buildable things.

Using design principles of nature is much faster and easier than researching mentor organisms, though it does not provide the deeper connection to nature.
To ideate from principles, find a list of biological design principles, such as Biomimicry 3.8’s “Life’s Principles.” Steven Vogel’s list in Cats’ Paws and Catapults, or this chapter. Select one or more relevant principle. Brainstorm buildable ideas from that principle. Repeat as necessary.
Principles can also be used to assess how biomimetic a design idea is, though this is highly subjective.

The Cradle to Cradle (C2C) concept takes natural systems as a source of inspiration, striving toward a positive vision where human society and industry regard waste as “food” for new cycles of use, and are powered entirely by renewable energy. Cradle to Cradle is not about efficiency but about effectiveness—waste need not be minimized if it is food for other cycles, providing positive regenerative impacts. However, this is difficult to achieve in practice. The Circular Economy concept elaborates on the Cradle to Cradle model, prioritizing longer product lifetime and recovering whole products over material recovery through recycling.
The Circular Economy also combines ecological thinking with economic thinking, making a business argument for sustainability.
Both concepts have been very influential in shaping the way we think about design for sustainability.

The validity and reliability of four prevalent reparability scoring systems has been investigated by comparing scores of ten smart phones and six vacuum cleaners versus empirically measured repair times, as well as comparing hypothetical ideal and problematic scenarios. Ease of disassembly methods was also assessed for five smart TVs, four washing machines and six vacuum cleaners. The scoring systems studied were the French Reparability Index (FRI), Joint Research Centre Scoring System (RSS/JRC), iFixit, and ONR19202. Overall scores of products across scoring systems were relatively well correlated, indicating a fair amount of overall reliability. However, the variability in scores for the best and worst case of the same product was often larger than the differences between products. Validity was good for products that are easily repairable, but scorecards often failed to score low when repair is infeasible or too expensive. Repair scores greatly depend on disassembly; since some scorecards count numbers of disassembly steps and other scorecards use proxy times, these two methods were compared against empirical disassembly times for five vacuum cleaners, five televisions, and four washing machines. The proxy time method was found to be highly accurate for all three product categories; the steps method was less so. It indicated the relative ease of disassembly well for washing machines, but not for televisions or vacuum cleaners. Finally, this study proposes improvements to scoring methods, including a limiting factor approach and the development of clearer protocols, to ensure the scoring systems are robust, reliable, and can effectively guide sustainable product design.