The biopharmaceutical industry is booming from the success of biologics. Currently, biologics represent the fastest growing sector in the global pharmaceutical market, generating revenues of $231.2 billion in 2017. This market is projected to reach $479.7 billion by 2024 at a compound annual growth rate (CAGR) of 10.9%. Over the next six years, monoclonal antibodies (mAbs) are predicted to rise, taking a leading position among a diverse array of biological products. Monoclonal antibodies are anticipated to capture 46% of the total biologics market share at a CAGR of 11.9%.1
Treatment potential and the associated financial rewards have fueled the search for next-generation biological therapeutics. However, drug discovery and development is a long, difficult and expensive process. Biologics, given their inherent complexity, impose unique challenges to this endeavor. The fundamental challenge facing biopharmaceutical drug innovators is how to optimize their research and development (R&D) efficiency and productivity from early-stage discovery to commercial manufacturing. There is a growing trend towards earlier decision-making so that drug candidates fail earlier, especially during early-phase discovery and development. This, in turn, reduces overall development costs.
In general, drug discovery begins with target identification and validation, followed by assay development, which is used to determine binding and/or modulations of the target. The assay is then performed over a pool of potential candidates to generate lead compounds that interact with the target. There are often repeated cycles of refinement assays, which narrow the pool of leads by improving their biophysical and biochemical characteristics, making them suitable for human trials.2 Typically, there is a 5.5-year time interval between the start of a research project to a phase IA clinical trial, including 4.5 years of discovery research and 1 year of preclinical testing.3 It is usually more costly to develop biologics than small molecule therapeutics.
One approach to improving drug discovery efficiency is to select better biological targets for the disease. This strategy requires a deep understanding of the pathogenesis of the underlying disease, as well as the biology of the target. It is commonly believed that better disease targets are essential to develop more effective therapies, improve R&D efficiency, boost success rate, and reduce costs.
Two key questions should be asked at the onset of seeking a biological targeted therapeutic. First, is there sufficient evidence to link the target to the disease? Second, is the target viable for biological therapeutics, antibody-based or other formats? A thorough data mining of available biomedical data is usually a good starting point. A wealth of information can be gained from a variety of data sources such as publications, patent information, gene expression data, proteomics data, transgenic phenotyping and compound profiling data. Further, phenotypic screening methods are gaining traction in antibody discovery as a means to identify either disease-relevant targets or antibodies that are eliciting desired physiological responses.4, 5 To ensure the accuracy of the target, a multi-validation approach is necessary by collecting enough evidence to support target rationale and performing experiments using knock-out cell lines and/or animal models to validate the target.4
In the search for better disease targets, the National Institutes of Health (NIH) launched a public-private venture program, the Accelerating Medicines Partnership (AMP) in 2014, to identify and validate promising biological targets for new diagnostics and therapies at reduced time and cost. As of 2018, 12 biopharmaceutical and life science companies and 13 non-profit organizations along with NIH and the U.S. Food and Drug Administration (FDA) have joined the AMP. Current AMP research projects are focused on four areas: Alzheimer’s disease; type 2 diabetes; autoimmune disorders of rheumatoid arthritis and lupus; and Parkinson’s disease.6 The AMP represents a trend of increasing collaborations between governments, industry, academia and non-profit organizations to promote scientific communication, information exchange and data sharing, and thus accelerating drug discovery and development.
Another approach to speeding drug discovery relies on the development of more robust, sensitive and accurate assay technology that simplifies and expedites the process. In a traditional antibody discovery stage, potential antibodies go through a series of sequential assays: primary screens for binding and specificity in biochemical assays (e.g. ELISA); secondary cell-based binding assays; functional assays; and optimization screens composed of three steps — optimization binding assay, specificity assay and cell-based binding assay. There are several limitations embedded in this workflow. First, it is resource-intensive in terms of time, instrument requirements, and reagents. Second, denatured proteins are used in biochemical assays, which can lead to missed hits. Lastly, data inconsistency and errors are likely to be introduced between each step.7 Technology advancement is needed to streamline the antibody screening process with improved simplicity and efficiency.
In addition, a more sensitive primary high-throughput screen (HTS) that can tolerate crude preparations is quite desirable. In the initial screen, protein libraries are often present in bacterial lysates or extracts, or hybridoma supernatants, rather than purified forms. Components in bacterial preparations (i.e. bacterial by-products) and hybridoma supernatants (i.e. serum and growth factors) can interfere with HTS performance resulting in decreased sensitivity and accuracy.5
Moreover, the requirement for using purified antibodies or IgG reformatting (the technique for reformatting phage-displayed antibody fragments to full-length IgG) for functional cell-based assays has often been a bottleneck in antibody lead generation and selection. Several strategies have been proposed to address this issue including reformatting antibody libraries, IgG display on mammalian cells, and screening in IgG product format.5
Targeting intracellular molecules has been a long-standing challenge for biologics. Their large molecular weight and high structure complexity impede them to effectively cross the cell membrane and interact with intracellular target consequently. On the other hand, intracellular protein-protein interactions (PPIs) offer a rich pool of potential therapeutic targets, awaiting next generation biologics to make a footprint.
Many approaches have been raised to enhance intracellular delivery of biologics including protein engineering, nanoparticles, antibody engineering and novel drug delivery systems. One promising method involves coupling biologics with cell-penetrating peptides or protein transduction domains (PTDs), such as Tat, SynB, and penetratin. These cationic peptides are able to translocate across cell membranes and have been used to deliver peptides, oligonucleotides and proteins into the cells.5
In recent years, antibody fragments such as a single-domain antibody (sdAb) have gained much attention as the new generation of antibody drugs. In contrast to full-length Abs, antibody fragments are much smaller in molecular size with less structure complexity. They have showed better penetration into solid tumors and tissues. Engineering antibody fragments into functional intracellular antibodies, or “intrabodies,” may provide an alternative to intracellular delivery. One disadvantage of antibody fragments lies in their shortened half-life. Several half-life extension techniques can be used to address this issue, including PEGylation and albumin conjugation. In addition, antibody fragments can also be used as building blocks to generate larger multivalent or multispecific molecules.5
The brain is one of the least accessible organs in the human body and remains a challenging target for biologics due to their inability to cross the blood-brain barrier. One purpose of improving biologics delivery to the CNS is to target brain tumors; antibody-based therapy offers more specific treatment regimen and thus may achieve better treatment results and prognosis. A number of methods have been developed to achieve this goal, including invasive techniques (i.e. direct injection, mechanical or biochemical disruption of the BBB) that carry apparent risks and pharmacological modifications such as conjugation to a “molecular Trojan horse,” cationization and encapsulation in liposome nanoparticles.5
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