The drug discovery industry has been through a tumultuous transformation over the past 10 years. The dust now appears to be settling, and out of it new business models, advances to existing methods and key enabling technologies have emerged.
While the objectives of drug discovery have not changed, the way the industry achieves them has changed dramatically. The conventional silo-based business model has transitioned to a more open and collaborative model built around adaptability and innovation where companies, research organisations and academic partners can all share in the development of a new drug. The traditional approach of identifying a single disease target and then developing a target-specific compound has not filled the drug candidate pipeline with successful candidates as expected. We are now confronting more difficult and complex debilitating chronic diseases that require a different approach. It is generally agreed that efficient drug discovery and development requires a deeper understanding of the biology of disease and applying technologies to get this information earlier in the process is expected to lower costs, reduce attrition rates and ultimately result in better drugs. My predictions for the future of drug discovery in five years are from the perspective of a technology platform provider with products focused to facilitate the study of cells, and the components of cells, to help scientists gain a better understanding of normal and disease processes.
Human biological systems are complex, consisting of genes, proteins, cells and other components working together in intricate networks needed to sustain life. Genomics and proteomics provide important clues to understanding the biology of disease, but alone do not provide a complete picture.
A deeper understanding of the biology of disease can be derived by directly examining cells and cell constituents to systematically determine both the disease genotype and the drug response phenotypes. Cell-based assays that measure processes within individual cells and multiplex bead-based assays that measure the interactions of components of cells such as individual proteins are critical for understanding disease mechanisms. Cellbased assays have played an increasingly important role in drug discovery, driven largely by advances in cell analysis tools such as high content imaging, flow cytometry, and fluorescent probes. Finding an initial niche in secondary screening as well as toxicity testing, cell-based technologies today are ubiquitous throughout the drug discovery process.
Multiplex bead-based assays yield a wealth of information on the roles of multiple proteins and other biomolecules in diverse biological processes, providing insight into the identification and assessment of disease progression. While bead-based assays have gained widespread use later in the drug development process and in clinical diagnostics, they have not been used much in large scale screening applications due to reagent cost for the large number of samples needed to screen a compound library and lack of available high throughput tools to analyse them. In addition, the ability to combine bead-based assays with cell-based assays in the same well, provides new insight such as simultaneously measuring cell function and protein secretion.
In the traditional ‘target-based drug discovery’ approach, scientists identify and study individual molecules and their mechanism of action. These have performed poorly at identifying first-in-class medicines when compared to ‘phenotypic drug discovery’ methods. High content cell-based assays provide rich biological information earlier in the drug discovery process and since most are multi-parameter and analyse single cells they can be considered inherently ‘phenotypic’. I expect that drug discovery will continue to evolve to a balanced approach that leverages the strengths of both phenotypic and target based strategies.
To unravel complex biology, the generation of rich, multi-parameter phenotypic data is needed which will drive the continued growth of high content technologies. Imaging-based high content systems have been an effective tool for analysing adherent cells. Cells in suspension and multiplex bead assays, however, are not amenable to imaging and this has left the development of therapeutics in areas such as the immune system, underserved. The information contained in the large complex multi-parameter datasets generated by these systems can only be realised with analytical methods and software tools to effectively integrate, analyse, interpret and share them. The ability to provide deep insight into cellular function early in the discovery process will grow and be increasingly important toward lowering costs, reducing attrition rates and improving healthcare outcomes. As a result, technologies such as IntelliCyt’s iQue® Screener platform, which enable high content as well as high throughput, screening of cell and bead-based assays will be more broadly incorporated into the drug discovery process.
Along with the growing use of cell-based assays comes the need for better diseaserelevant cell types. The ability to test drug candidates in cells that are representative of the disease and environment they function in will result in better understanding of disease. We expect that technologies such as humaninduced pluripotent stem cells; cell lines derived from gene-editing technologies; and primary cells obtained from patients with a range of genomic backgrounds will result in more disease relevant cell lines. Many of these cells are scarce (eg human primary cells) and/or expensive to develop and are often provided in a suspension format. As a result, the demand for platforms systems which can analyse small sample volumes of suspension cells to study these cell types will continue to expand over the next five years.
Advances in personalised/precision medicine approaches will continue. The first wave of personalised medicine has leveraged advancements in genomics to utilise a patient’s genetic information to support earlier diagnosis, therapeutic decision-making and development of patient-specific treatments. While there are some high profile successes of this approach, personalised medicine is not yet in widespread use. The promise of personalised medicine is acting as an engine of innovation in drug discovery and is driving more synergy between drug discovery research and the clinic. I expect that successful personalised treatments will result from integration of genomic and high content cell-based approaches from both research and the clinic that utilise a combination of an individual’s genotype and phenotype.
There has been a number of astounding success stories recently in engaging the body’s immune system to treat cancer and immuno-oncology has emerged as one of the most exciting developments in cancer in a long time. These breakthrough therapies have the potential not only to revolutionise the way cancer is controlled and treated, but potentially cured. There are an unprecedented number of collaborations and deals among pharma, biotech and technology companies combining efforts toward successful therapies. I expect there will be a number of successes resulting from these over the coming years that will lead to genuine cures for many forms of cancer within the next 10 to 15 years.
In summary, I expect that a growing pipeline of new drugs will be discovered and developed over the coming years by better understanding the biology of disease through the effective application of high content cellbased and multiplex bead-based technologies to get this information earlier in the drug discovery process. Combining results from high content technologies with other ‘omic’ technologies will provide a more complete holistic view and understanding of the biology of disease. As an industry, to get to a new age of drug discovery and development it will require innovative and adaptable collaborations among companies, research organisations and academic partners who can all contribute and share in the success of bringing new treatments to the world to truly improve healthcare outcomes.