Sustainable Medicines Manufacturing

Global pharmaceutical supply chains are under unprecedented strain. Recent events such as the COVID-19 pandemic and geopolitical tensions have exposed vulnerabilities driven by raw-material shortages, energy volatility and increasing regulatory expectations, including the EU’s proposed Critical Medicines Act proposed by the European Commission in March 2025. At the same time, the pace of drug development continues to accelerate. Funders expect faster chemistry manufacturing and controls (CMC) development, seamless technology transfer, real-time quality oversight, and digital-ready compliance from both in‑house networks and CDMOs. In addition to this, sustainability can no longer be treated as a parallel agenda. Instead it must be embedded from the outset in order to meet increasing environmental demands from Governments and align with ambitious targets laid out across the private sector.

Perspectives from established academic–industry consortia such as CMAC (1) are hugely valuable as they have assembled a critical mass (research teams, leaders from large pharma, CDMOs and regulators), are technology agnostic, typically operate under pre-competitive collaboration models and are at the forefront of critical manufacturing developments. A dedication to advancing world-class research, providing key skills to the future workforce and validating innovative technologies provides a unique resource for the pharma community and also creates opportunities to rethink medicines manufacturing as a digitally enabled, skills‑rich, low‑carbon system that is both resilient and globally connected.

Redefining Agility

As much as we would like to think otherwise, Pharma doesn’t move fast enough for pandemics like COVID-19. Amidst an antibiotics crisis, where game changing developments like Penicillin are rare, there are huge gaps which need to be filled. Well-established drugs have unstable supply chains: Paracetamol manufacture is essentially non-existent in Europe for example. The US resorted to treating the supply of paracetamol as a security issue during COVID-19, a drug which has a well-known synthetic route. Whilst reshoring or regionalisation can improve security for critical products, fully localised supply chains are rarely economical for complex APIs and dosage forms. A more pragmatic approach combines selective regionalisation for critical steps with globally diversified sourcing. End‑to‑end visibility allows manufacturers to anticipate disruption and intervene earlier, supporting resilience without sacrificing efficiency.

Agility is not just about speed. It encompasses modular and flexible capacity, accelerated technology transfer, and digitally enabled release strategies. Continuous and hybrid manufacturing platforms, standardised equipment, and modular facilities can shorten changeover times and support rapid scale‑up or scale‑down in response to demand fluctuations. Continuous manufacturing remains an effective approach for enhanced operations: de-risking complete batch failures, offering improved product consistency and allowing key unit operations to be linked. Advanced process monitoring allows quality decisions to be made in real time and these can be driven by intelligent, AI control systems which continue to improve at a significant rate. Furthermore, automation has been making significant headway, displacing mundane tasks over 8 hours by robotics working 24/7.

Large pharma organisations continue to operate on mixed models, some completely outsourcing drug manufacture to CDMOs and others retaining capabilities in-house. However, new contracting and partnership models are also emerging, where strategic partners can co-develop processes and share data responsibly, as opposed to traditional, transactional relationships. Much of this is of course driven by cost – largely inflation in energy and raw materials – but also in recognition that more agile and innovative approaches are needed. Critically, audit‑ready facilities in 2030 will not only be defined by their physical operations, but also the maturity of their digital systems and governance.

The Importance of Data

Data and AI are no longer future aspirations; they are already delivering value in medicines manufacturing. Quality by digital design principles, supported by data‑rich development strategies, allow critical quality attributes (CQAs) and process parameters to be defined and controlled more effectively. However, technology alone is insufficient. The quality, governance, and contextual understanding of data are critical. Cybersecurity of course, remains a key consideration and frameworks such as ISO 27001 and independent assessments like CyberVadis are increasingly important for demonstrating that sensitive data are protected and managed responsibly. Data is a key asset for any organisation and must be organised and managed well. This is where collaboration between industry and academia is particularly powerful: combining specialised expertise with advanced data science to deliver solutions that are both technically validated and operationally relevant. Educating and teaching staff on AI and data management will also help alignment and ensure data is being used properly.

Data repositories are still highly siloed however. Where academic organisations tend to have more freedom to operate, private companies have limited options around sharing proprietary information. The challenge is that predictive models can only be improved by incorporating real-world examples as opposed to being limited by model systems. Theoretical and predictive experiments are increasingly powerful and cyberphysical systems are redefining Pharma R&D. Individual organisations are already creating data Knowledge Graphs which are tools to manage standardised data collection and (automated) processing and facilitate predictive experiments. The real benefit will be in linking such knowledge graphs across organisations, whilst respecting proprietary information and IP.

Working Towards Net Zero

Greenhouse gas emissions (GHGs) from the pharma industry equate to around 52 Mt CO2 per annum (20 % of the total industrial carbon footprint), the bulk of this arising from drug product manufacture but a significant portion also stemming from distribution. This has continued to grow and is the highest E factor amongst chemical using industries (up to 100 kg of waste per kg of product). This is largely a consequence of the constrained timelines for product and process R&D to meet the demands of clinical testing and safety, leading to sub-optimal processes and excess waste generation.

Most pharma manufacturing organisations have been taking steps to reduce GHG emissions across Scopes 1, 2 and 3 in line with environmental pressures however common mistakes such as missing or poor quality baselining, limited consideration of indirect (Scope 3) emissions and inadequate allocation of dedicated resources are still taking place. It is therefore critical that organisations plan their activities around the following key areas. Infrastructure: flexible operation of airflow systems, lighting and heating. Energy efficient technologies: standby modes, sustainable consumables, cleaning and waste generation considerations. Smart technologies: robotics, automation, simulation/modelling and data management/streamlining. Culture: empowering end users to adopt sustainability practices across their activities. Travel: clear policies and robust technologies for remote communication. These areas are often tackled individually however a whole systems approach will increase the likelihood of greater success.

Skills: The Foundation of Transformation

None of these advances are possible without the right skills. The pharma sector faces a growing need for multidisciplinary individuals who are proficient in manufacturing science, digital technologies, data analytics, and sustainability principles. Upskilling the existing workforce and training the next generation is therefore a strategic imperative. Industry increasingly looks to academic consortia not just for technology development, but for talent pipelines, flexible training models, and translational research environments that reflect real manufacturing challenges. Doctoral training schools, especially those spanning multiple disciplines, are an excellent example of skills development platforms and have a vital role in equipping the future workforce with the right tools.

Looking Ahead to 2030

By 2030, quality and supply‑chain excellence will be defined by integration: integrated data, integrated partnerships, and integrated sustainability objectives. Leaders will differentiate themselves through digital maturity, flexible and modular manufacturing platforms, strong cybersecurity and data governance, and a workforce equipped to operate at the interface of science, technology, and sustainability.

For academia, industry, and regulators alike, the challenge is to move beyond incremental improvement and embrace systemic change. Sustainable medicines manufacturing is not simply about reducing environmental impact; it is about building a resilient, agile, and trusted system capable of delivering high‑quality medicines to patients, reliably and responsibly, in an increasingly uncertain world.

References and notes

1. https://www.cmac.ac.uk/