19th August 2026

As biopharma manufacturers face unprecedented demand, the therapies they are developing have also become increasingly advanced. Cell and gene therapies are no longer experimental treatments, but their rise as mainstream medical interventions has put an added sense of pressure on the industry to scale up production without sacrificing precision and quality. This has laid the foundations for something of a technological revolution in bioproduction, spurred on by a convergence of production challenges and clinical promise.

But how can the industry, and the biologics sector in particular, meet the demands of this new pharmaceutical landscape?

The Robotics Revolution in Pharmaceutical Manufacturing

Automation has been at the heart of transformation in a huge number of industries, and pharma is no exception. The sector’s global market for robotics reaching $209.48 million in 2024, [1] and set to more than double in the subsequent decade, with North America holding the largest market share, [2] and the Asia-Pacific boasting the fastest projected CAGR.

This substantial growth trajectory reflects the increasing application of automation across production facilities, alongside advances in robotics which are now better equipped to address rising labour shortages in certain skilled manufacturing roles. At present, picking and packaging are the most widely used form of robotics in the pharma sector, but their integration extends beyond simple task automation.

Modern pharmaceutical manufacturing processes have become more dependent on sophisticated robotic systems to handle delicate biological materials, maintain sterile environments and execute complex, multi-step processes with minimal human intervention. These are particularly crucial capabilities for bioproduction, where contamination risks and process variability all but demand unprecedented levels of precision and consistency.

The Autonomous, AI-Driven Future of Biomanufacturing

If robotics has driven much of the change to biologics manufacture, then artificial intelligence represents its next frontier, offering improved accuracy, reproducibility and efficiency in the research and development stage. Taking inspiration from the automotive industry's progress with self-driving vehicles, biopharma companies are developing AI-guided laboratories [3] which operate with increasing independence, even beginning to outperform human researchers in specific applications.

According to a survey, 77.3% of biopharmaceutical manufacturers [4] indicated that their organisations are already using AI in research and manufacturing, with most companies having adopted it in the last one or two years. This rapid adoption underscores AI's transformative potential across the manufacturing lifecycle; as autonomy finds holistic use cases across of bioproduction, machine learning algorithms are making process optimisations [5] in real-time, adjusting variables like temperature and pH to maximise yield and product quality. Predictive maintenance systems can minimise costly downtime by analysing performance data [6] from equipment to anticipate failures before they occur, while computer vision systems are able to inspect products and identify defects which would be invisible to the human eye.

The pharmaceutical manufacturing industry is transitioning through distinct stages of autonomy, with most companies are currently adopting partial automation, while using data to support decision-making. However, leading organisations such as Genentech, AstraZeneca and Recursion have significantly advanced their usage, incorporating AI into their hypothesis generation, test execution and designing further rounds of experiment, all with minimal human intervention, creating what the CEO of one autonomous laboratory company described as “the Waymo version” of traditional scientific spaces.

Cell Therapy Manufacturing: Scaling Personalised Medicine

The cell and gene therapy manufacturing market is set to reach a predicted value of $160.0 billion [7] by 2035, reflecting both the clinical promise of these treatments and the substantial manufacturing challenges they present. Manufacturing these therapies relies on a high variability of cell types and gene-editing techniques, which complicates any efforts to streamline production processes. [8] The conditions in which these treatments are created must be stabilised in order to ensure that their efficacy remains unimpeded, creating further issues around devising reliable and scalable methods to preserve, transport and administer delicate cellular products

Starting material from different donors also produces cells with varying metabolic profiles and capabilities, while still maintaining consistent results. As such, automation has emerged as equal parts necessity and challenge for scaling the manufacture of cell therapies, with a pivot away from batch manufacturing towards continuous production proving to be an especially promising alternative. The number of commercial-stage cell therapies has only grown in recent years, and increased investments in manufacturing infrastructure have allowed biopharmaceutical companies to fully embrace modern automation solutions. [9] As such, robotics play a crucial role in standardising processes, lowering costs and meeting large-scale manufacturing requirements.

Capacity Expansion and Manufacturing Innovation in mRNA Production

Following the COVID-19 pandemic, the market for the synthesis and manufacture of mRNA vaccines has seen substantial investment in order to expand capacity. Unlike traditional biologics, mRNA drugs don’t require the use of living cells, theoretically making them simpler to manufacture. However, scaling up production to meet demand remains challenging, whether through unreliable process [10] control or complex manufacturing methods which are as-yet unstandardised.

The complexity of mRNA synthesis [11] and manufacturing also presents a major challenge for market participants, with each step requiring precise control to ensure quality and stability. Accomplishing this at scale makes an already fraught process even more difficult, requiring specialised raw materials which can easily be subject to shortages or price volatility, with access to high-quality and GMP-compliant raw materials for mRNA production entirely dependent on a limited number of reliable suppliers

The integration of automation and digital technologies emerges as a crucial opportunity. Automating synthesis, [12] purification, and filling systems can reduce the amount of human intervention, improving process reproducibility in a way which can support scale-up. With monitoring conducted digitally, quality control and regulatory documentation is enhanced through real-time data analytics and process modelling, which can improve compliance, quality and reputation.

Broader Biologics Manufacturing Trends Shaping the Industry

The increasing adoption of single-use bioprocessing systems has been a gamechanger for the pharma sector at large, heading towards a predicted market value of $128.24bn by 2033. [13] Using disposable components like bags and filters rather than components made of bulkier materials, these systems increase the flexibility of production scale-up, lowering the chance of cross-contamination and cutting the time it takes to set up production.

Continuous bioprocessing represents another transformative trend, integrating all stages of manufacture within a single facility, in one interrupted run. This approach eliminates built-in production gaps, shortening manufacturing times from months to days, and has been increasingly enhanced by AI-driven process control. As continuous production lines generate more data than any team can track manually, companies are driving adoption of these systems which can learn from that data and adjust its processes in real-time. They are also able to process deviations before they impact product quality and strengthen real-time release testing.

Despite remarkable progress, the bioproduction sector still finds itself in need of higher levels of investment [14] to fully realise its potential, putting smaller firms at considerable disadvantages in their early stages. Meanwhile, the technical complexity of manufacturing cell therapies can make it difficult to integrate robotics into existing processes, while staff will need to be upskilled in the technology to ensure its smooth adoption. Beyond technical considerations, bringing biologics to global scale [15] requires harmonisation around any regulatory measures, as well as standardised logistics to make sure the treatments themselves maintain their efficacy. This will ensure more consistent clinical trials and commercial distribution across multiple territories.

The industry has also confronted warnings about the possibility of "catastrophic success" [16] in cell therapy, where the high cost of manufacturing and inefficiencies in manufacturing and logistics could limit patient access even as clinical efficacy improves. With forums like the Bioproduction Zone [17] at CPHI Milan giving the industry a platform to unite under one roof to compare technologies and identify collective paths ahead, industry experts have more opportunities than ever to get behind this revolution in personalised medicine. The high cost of manufacturing mirrors the initially high cost of production for protein therapeutics – an example which shows that efficiency increases can predictably lead to lower costs, making these vital treatments more accessible than ever.

As the industry navigates challenges of scalability and cost, integrating advanced technologies into manufacturing processes will become a critical differentiator in the wider pharma market. The introduction of robotics, artificial intelligence and sophisticated bioprocessing technologies is fundamentally reimagining the modern state of bioproduction, facing increased scrutiny over the sustainability of these methods over time. Ultimately, the coming years will demonstrate whether the industry can scale these innovations successfully to meet their ultimate test: maintaining the quality, safety, and affordability that patients deserve.