Physicochemical, biological, functional and toxicological characterization of the European follow-on glatiramer acetate product as compared with Copaxone.

For more than 20 years, Copaxone (glatiramer acetate, Teva), a non-biological complex drug, has been a safe and effective treatment option for multiple sclerosis. In 2016, a follow-on glatiramer acetate product (FOGA, Synthon) was approved in the EU. Traditional bulk-based methods and high-resolution assays were employed to evaluate the physicochemical, functional, and bio-recognition attributes, as well as the in vivo toxicity profile of the active substances in Copaxone and Synthon EU FOGA lots. These tests included quality control tests applied routinely in release of Copaxone lots, as well as additional characterization assays, gene expression studies and a rat toxicity study. Even though the Synthon FOGA was designed to copy and compete with Copaxone, the active substances were found to be similar in only 7 of the tested 14 (50%) methods (similar is defined as within approved specifications or within the inherent microheterogeneity range of tested Copaxone batches, or not showing statistically significant differences). With additional methods applied, consistent compositional differences in attributes of surface charge distribution, molecular size, and spatial arrangement were observed. These marked differences were concordantly observed with higher biological activity of some of the Synthon EU FOGA lots compared with Copaxone lots, including potency and cytotoxicity activities as well as gene expression of pathways that regulate apoptosis, IL-2, and inflammation signaling. These observations raise concerns for immunogenicity differences, particularly in (repeated) substitution settings. Another orthogonal finding demonstrated increased frequency of injection-site local toxicity observations for the Synthon EU FOGA in an in vivo daily dosing rat study, thus warranting further qualification of the link between compositional and functional differences in immunogenicity, and potential impact on long-term efficacy and safety.

Drug repurposing from the perspective of pharmaceutical companies.

Drug repurposing holds the potential to bring medications with known safety profiles to new patient populations. Numerous examples exist for the identification of new indications for existing molecules, most stemming from serendipitous findings or focused recent efforts specifically limited to the mode of action of a specific drug. In recent years, the need for new approaches to drug research and development, combined with the advent of big data repositories and associated analytical methods, has generated interest in developing systematic approaches to drug repurposing. A variety of innovative computational methods to enable systematic repurposing screens, experimental as well as through in silico approaches, have emerged. An efficient drug repurposing pipeline requires the combination of access to molecular data, appropriate analytical expertise to enable robust insights, expertise and experimental set-up for validation and clinical development know-how. In this review, we describe some of the main approaches to systematic repurposing and discuss the various players in this field and the need for strategic collaborations to increase the likelihood of success in bringing existing molecules to new indications, as well as the current advantages, considerations and challenges in repurposing as a drug development strategy pursued by pharmaceutical companies. LINKED ARTICLES: This article is part of a themed section on Inventing New Therapies Without Reinventing the Wheel: The Power of Drug Repurposing. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v175.2/issuetoc.

Letter to the Editor response: Nygaard et al.

The article by Nygaard and others (2016) proposes that applying batch correction approaches to microarray data from studies with unbalanced designs may inadvertently exaggerate the differences observed. In seeking to illustrate their point, Nygaard and others (2016) utilized a dataset (GSE61901) from a study we published (Towfic and others, 2014) and showed that one analysis pipeline utilizing the traditional approach to batch correction (ComBat) yielded over 1000 differentially expressed probesets, while an alternative approach proposed by Nygaard and others (2016). (utilizing batch as a fixed effect and averaging technical replicates) recovered 11 differentially expressed probesets.

Use of genetic technologies to compare medicines.

In order to ensure that patients receive the safest and most effective medicines possible, it is often necessary to compare medicines and assess the extent to which they are similar in their clinical impact. Full clinical trials with appropriate endpoints remain the only method to compare the clinical impact of two medicines with absolute certainty. Other available methods (including physicochemical analysis, genomics, and transcriptomics) can provide partial information about certain aspects of a medicine's biological impact, with possible clinical implications. Especially for biologics and non-biological complex drugs, which are more difficult to characterize by physicochemical means than small molecules, genomics and transciptomic studies can yield valuable insights for physicians, regulators, and drug developers. In this review, we cite and summarize a variety of studies that exemplify the emerging science of applying genomics and transcriptomics technologies to compare medicines. We discuss key aspects of experimental design, conduct of genetic assays, and advanced data analysis, all of which are critical for the successful execution of such studies. Finally, we propose new areas for which such studies can be applied to maximize patient benefit and reduce safety issues.