Since the start of the genomics era, we have transformed how we understand disease. We have gained insights into the genetic and epigenetic modifications that drive pathology. Moreover, we have found ways to advance translational science, facilitating the development of new diagnostics and treatments. And now, as the genomics era continues to unfold, there is a growing emphasis on the early detection of genetic and epigenetic changes. This transformation is expected to help clinicians intervene earlier in the course of disease.
Central to this transformation has been the use of oligonucleotides (oligos) to facilitate analytical and diagnostic methods ranging from DNA sequencing to microarrays to fluorescence in situ hybridization assays. Beyond characterization and diagnosis, however, the genomics era is marked by a rapid transformation of clinical intervention.
There are efforts to shift treatments from ameliorating disease to addressing the underlying genetic causes of disease. These efforts are best exemplified by gene therapy and gene editing applications, which are designed to overcome disease-causing mutations, and by RNA-based applications, which have been developed more recently and include mRNA vaccines and mRNA protein replacement therapies. For these applications, oligos are no longer simply analytical reagents but instead are active pharmaceutical ingredients (APIs).
Oligo-based therapeutics
One appeal of oligo-based interventions is the sequence specificity they offer. Drug developers can rapidly adapt any molecule to changing circumstances by simply changing the sequence, reducing the complexity of reengineering the API. This allows drug developers to swiftly address different genetic profiles between patients with the same disease, or to address the rise of viral variants, as was shown with the development of SARS-CoV-2 vaccines. It is not enough, however, to say that “an oligo is an oligo is an oligo,” and that sequence changes will not affect an oligo’s attributes as a therapeutic.
Although the quality standards for reagent-grade oligos have always been high, the development of oligos as APIs demands increased sensitivity, precision, and accuracy from analytical technologies and methods to ensure their safe and effective use as well as manufacturing quality.
For example, mass spectrometry can help identify impurities within an oligo sample, and it can confirm oligo sequences, even differentiating isomeric molecules where single bases have been swapped. Similarly, analytical software is continuously improving to streamline data processing, enhancing characterization throughput and accuracy.
Monitoring modifications
Aside from sample purity and sequence issues, oligo characterization can be further complicated by chemical modifications of an oligo’s nucleotides and backbone. More than simply artifacts of synthesis or processing, many of these modifications can have biological significance and, therefore, therapeutic implications, as evidenced in the growing fields of epigenetics (DNA) and epitranscriptomics (RNA).
Pseudouridine, for example, has been shown to improve mRNA stability and can facilitate increased protein expression levels. Modification of the oligo backbone (for example, with 2¢-methyl or 2¢-fluoro units), meanwhile, can make RNA molecules more resistant to enzymatic degradation and help maintain important RNA structures, thereby influencing biological activity and pharmaceutical parameters such as dosing.
Chemical modifications can also reduce the likelihood of a therapeutic RNA inducing an innate immune response when introduced to a patient, improving safety. These modifications increase the demand for stringent tools to accurately assess their impact on the functional activity and stability of the oligos. Mass spectrometry and sequencing methods can identify the presence and nature of such modifications and their locations within oligos. Cell analysis techniques, meanwhile, can offer functional, therapeutic, and safety insights.
By pulling data from these disparate technologies, drug developers can use computational biology and machine learning to construct and test molecular models to enhance the pharmaceutical design process. Such models can improve our understanding of the critical success parameters for the current generation of oligo-based therapeutics and increase the likelihood of success for subsequent generations.
Sergey Vlasenko, PhD, is associate vice president, pharma and biopharma, Agilent Technologies.