Navigating the changing landscape of drug discovery: the role of collaboration, biologics and data

Author: Saskia Hoving

Editor-in-Chief

The way that drug candidates are identified and developed is changing rapidly. Advancements in data science, AI, and biologics have disrupted the industry and paved the way for partnerships between industry giants and more nimble start-ups. Data is no longer just an output of research; it’s now a powerful generator of new insights. The drive for faster drug discovery has placed greater emphasis on new sources of information. Based on research conducted by Maverick Publishing Specialists, this blog explores the factors driving these changes, the opportunities for start-ups, SMEs, and investors, and how data and information are pivotal for the future of drug development.

How the drug market shifted so quickly

For decades, there has been limited change in the organisations with the biggest influence in the pharmaceutical market, with big pharma firmly at the centre, with a high barrier to entry. But as new types of organisations enter the drug discovery industry, big pharma’s role is evolving through partnerships and collaboration to become a business ‘hub’ focused on commissioning, pipeline management, branding, and bringing drugs to market.

A significant factor in this changed position is the drop-off in the development of new blockbuster or broad-spectrum drugs. Pharma companies are instead facing a “patent cliff” with many highly lucrative medicines due to go off-patent this decade. Instead of blockbuster drugs, the market has shifted to seek more specialised areas with longer-term revenue, such as oncology, personalised medicine, rare and orphan diseases, neurodegenerative disease, and biologics.

Advances in molecular biology and medicine, such as gene editing and stem cell research, have moved the industry towards research and development of drugs that are biologically, rather than chemically, driven. These advances in biologic drugs that have given us mRNA vaccines (such as for Covid-19) and the ability to treat previously incurable late metastatic cancers.

While many big pharma companies have invested in biological drug development, biotech firms are now driving much of the innovation. Collaborating with biotechs, such as by providing funding and large-scale manufacturing, allows big pharma to stay competitive. According to IQVIA, two-thirds of drugs approved by the FDA now come from emerging biotechs. And, although biologics represent just 2% of US prescriptions, they account for 46% of spending on medicines, highlighting their growing significance.

Biologic drugs are expensive to develop and tend to have a much smaller patient base, but they can address previously incurable conditions, creating strong demand. Combined with an aging population with growing health demands, governments and insurers are seeking ways to reduce costs, further pushing for cost-efficiency in the pharma industry. This in turn has created more opportunities for contract research organisations (CROs) which provide outsourced clinical monitoring, statistics, pharmacovigilance and drug safety, and project management.

Data as the new key ingredient for drug discovery

The role of data in disease and drug discovery is undergoing a significant transformation, moving from simply being an output of research, to a source of new discoveries and a valuable product in itself. The exponential increase in the volume of research data, alongside advancements in bioinformatics, AI, machine learning, and virtual bench science have enabled huge leaps forward in computational drug discovery. These advances have led to the foundation of record numbers of AI-driven drug discovery start-ups, especially since 2018 when investment began to significantly expand.

DNA sequencing is now faster and cheaper than ever, creating opportunities for businesses emerging to interpret the findings. The microbiome is a hot topic, and since microbes contain around 100 times more genes than in the human genome, sequencing and investigating the gut is attracting start-ups looking to turn this knowledge into new medical treatments and medicines.

Alongside processing these new vast data sources, bioinformatics and computer models can also find new uses for existing drugs through data on the side effects of existing drugs. These technologies allow pharma and biotechs to bring new medicines to market rapidly with the advantage of a known safety profile for the drug.

Advancing research with varied data sources

The changes in how disease and drug research is conducted has also led to a change in the value of different information sources. There’s a growing need for deep data on specific topics or broad data across multiple areas, and to access new research faster than ever through non-traditional sources.

In precision medicine there is a need for very deep and detailed data sets on a specific topic, often referred to as “big small data.” For example, in cancer treatment, researchers may focus on data from a small subset of patients with a particular mutation to develop highly effective, personalized therapies.

Conversely, researchers are also seeking broader information covering both existing medical and clinical information and research on biological targets and mechanisms, but also molecular biology and materials science research.

Researchers cite a wide range of information sources as essential to ensure rapid access to new findings. Building up data banks with high-quality research is a top priority. The sources of valuable information today continue to grow, covering:

• Preprints, Journals, Table of Content alerts
• Meetings, Networks, Forums, Blog Content
• Business information/competitive intelligence, Patents
• Search and discovery services, Biobanks, Databases 
• Primary/Real-World Data

Dealing with a greater variety in information types and formats, as well as the vast increase in research output, is challenging to research teams. Text and data mining (TDM) is fast becoming a core capability and has become essential to extract insights from unstructured sources. With the explosion of literature, TDM is increasingly used not only to find new areas of investigation, but also to recycle research to gain previously undiscovered insights.

The future of drug discovery

The business of disease and drug discovery is rapidly evolving, driven by breakthroughs in AI, data science, and biologics. These changes, and the new businesses forming to take advantage of them, have encouraged big pharma to explore innovation and collaboration. As the demand for personalized treatments, biologics, and rare disease therapies grows, so too does the importance of data-driven discovery and the need to consider broad information sources.

Smaller organisations and start-ups specialising in niche areas, AI, or bioinformatics now have opportunities to innovate and disrupt the market which wouldn’t have been possible 10 years ago. In this new era, those who can harness the power of data, collaborate effectively, and remain agile will shape the future of drug discovery and development.

Resources at Springer Nature

To stay ahead in this rapidly changing field, companies and health organizations can benefit from the right resources and insights. Springer Nature offers access to a wide range of trusted research, curated databases and tools for analysing and applying data, helping companies stay updated with the latest advancements and accelerate their R&D efforts.

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