test
Sept 23-26, 2019
2019-09-23 12:30:00
Michael Selsted
Chief Operating Officer, Oryn Therapeutics
ORYN is developing macrocyclic peptide therapeutics. Orynotides are engineered theta-defensin analogs under development for autoimmune, inflammatory, and infectious diseases. This presentation will provide an overview of the preclinical and clinical stages of development for each of these applications.
Dr. Selsted’s laboratory is focused on the study of defensins in innate immunity and inflammation. Over his career, he and his colleagues identified three genetically related mammalian subfamilies (α, β, and θ) of defensins. θ-defensins are uniquely produced in Old World monkeys and are the only known backbone cyclized peptides in animals. Selsted’s team showed that θ-defensins have remarkable immunoregulatory properties and a lead compound has advanced to the clinic as first-in-class drug for rheumatoid arthritis. Other theta-defensin analogs are under development as treatments for inflammatory bowel disease, antibiotic resistant “super bug” infections, and as cancer therapeutics.
Zeke Nims
Discovery Lead, Orbit Discovery
Peptides are highly active biological molecules that, with advances in stability and delivery, present huge potential as drug candidates. They possess the advantages of biological and small molecule drugs due to their high specificity, low toxicity and low manufacturing costs. Currently, peptide therapeutics comprise just 5% of the pharmaceutical market and 1% of prescribed drugs. With an increased interest in the use of peptides as therapeutics comes the need for strategies to allow for the discovery of novel hit candidates, in a high throughput manner, from highly complex peptide libraries.
Current technologies for the discovery of novel peptide therapeutics include phage, yeast, ribosomal and mRNA display but these all hold their own limitations. Phage and yeast display are sensitive but a reliance upon a biological host can result in replication bias and interference from native host proteins. These systems are also restricted to the use of natural amino acids. In vitro technologies based on mRNA and ribosomal display have the ability to incorporate unnatural amino acids but are limited by small peptide copy number leading to a reduced detection of low affinity binders. Moreover, none of the current peptide display technologies can effectively address cell surface targets for the discovery of functional peptides.
The ORBIT in vitro display technology uses beads to present randomised peptide sequences and the DNA which encodes them, thereby linking genotype to phenotype, and combines the advantages of in vitro display, such as highly diverse libraries and a cell-free environment, with the high sensitivity of in vivo technologies. The ORBIT display platform presents thousands of identical peptide copies per bead allowing for the discovery of low affinity binders and allows for the incorporation of unnatural amino acids and the generation of cyclic peptides which can increase chemical diversity and improve stability, specificity and affinity. In addition to screening for binding peptides, the ORBIT platform can be adapted to screen whole cell surfaces for peptides which elicit functional cellular responses.
In summary, the ORBIT peptide display platform offers peptide drug screening with high diversity, sensitivity and plasticity, and has the potential to discover novel, selective and functional peptide therapeutic leads with a broad target coverage, including cell surface targets, for a wide range of diseases.
Zeke Nims obtained his Ph.D. from UMass Amherst, focused on plant natural product biosynthesis, followed by a postdoc at MIT investigating alkaloid pathway regulation to incorporate non-natural precursors to produce analogs. Zeke joined RaPharma in 2011, focused on interpretation of mRNA display selections using illumina sequencing, and then moved to IPSEN to set up a phage display laboratory. Zeke has been at ORBIT for 2 years, focused on optimizing and industrializing the ORBIT discovery platform.
Dale Thomas
Co-Founder, mytide therapeutics
Biological treatments have been playing an increasing in importance playing an increased roll within therapeutic advances over the past two decades. The utilization of synthetic peptides has been especially prevalent in diagnostics and personalized therapeutics, however, these fields have struggled with the slow pace of manufacturing due to bottlenecks in coupling, cleavage, and chromatography. Advances in laboratory automation have helped improve the productivity of expert scientists; however, these technologies have not been able to meet the demand for custom peptide sequences to enable rapid, cost-effective drug discovery, especially when compared to DNA synthesis. Inefficient synthesis techniques often take weeks, if not months, to produce the target molecule, becoming a major bottleneck in the drug discovery pipeline. Given that peptides are assembled from one reaction and a discrete number of building blocks, machine learning (ML) has the ability to drastically increase the speed of manufacturing by enabling sequence-specific optimization, significantly reducing the overall drug discovery time.
Mytide is leveraging process specific optimization within its Rapid Automated Computation, Coupling, Cleavage, and Chromatography Execution (RAC4E) platform to inform sequence-specific recipes. These models are enabled by closing the loop between data collection and manufacturing planning for each process step. Integrating optimization strategies into RAC4E serves as a foundation for efficient library development, leading the way towards high-throughput drug discovery pipelines using peptides.
Dale earned his PhD in automated continuous drug synthesis where he spanned both Mechanical Engineering and Chemical Engineering at MIT. He also completed his MEngM at MIT and BS at Maine Maritime Academy. In his research, he developed an array of flow chemistry platforms for the advanced synthesis of pharmaceuticals and advanced materials. At Mytide Therapeutics, Dale is leading a cross-disciplinary team of scientists, and engineers to overcome decades-long bottlenecks in peptide manufacturing. Increasing the speed, purity, and length of peptides promise to increase the rate of drug discovery and access to revolutionary biological treatment with the goal of positively impacting patients lives.
The peptide drug market is expected to generate $50B in revenue for companies but the FDA is concerned about the number of impurities that may be introduced in the synthetic process. Advances in chemical peptide synthesis have allowed the production of synthetic peptide drugs to become easier and more cost effective. However, the peptide manufacturing process can result in synthesis-related impurities that can introduce immunogenic epitopes within the amino acid sequence of the peptide resulting in an unexpected and undesired immune response against the drug. For instance, during the process of solid phase synthesis, impurities may arise as the result of incomplete coupling and side reactions. Several classes of impurities related to manufacturing and degradation pathways exist and include: amino acid insertions and deletions, truncations, isomerization, and side chain modifications. Any of these impurities can affect the safety and efficacy of these drugs and it is therefore important to assess any impurities that may be present after synthesis.
T cell- (thymus-) dependent (Td) responses play a critical role in the development of antibody responses to biologic therapeutics. Td responses, by definition, are contingent upon T cell recognition of therapeutic peptide-derived T cell epitopes through the basic processes of antigen processing and presentation. A fundamental requirement for peptides to be considered as T cell epitopes is that they bind to human leukocyte antigen (HLA) molecules. The HLA-peptide interaction involves binding of specific amino acid side-chains to pockets in the HLA molecule binding ‘groove’, an interaction that is well-characterized for many HLA. Briefly, the requirements for HLA binding can be codified in ‘motifs’ or patterns. Based on these characterizations, pattern-matching algorithms, such as the EpiMatrix algorithm, have been developed to screen amino acid sequences for peptides that will bind HLA. EpiMatrix can be used to screen both the drug API sequence and its known peptide-related impurities. When peptide-related impurities are unknown, modifications at each amino acid position in the peptide can be performed in silico, their immunogenicity risk can be predicted, and they can be assigned an impurity risk score. The “What if Machine” (WhIM), performs all possible changes to the natural amino acid sequence of the drug substance and measures their impact on the epitope content of the peptide.
Here we present a retrospective case study of Taspoglutide – a GLP-1 agonist that was under investigation for the treatment of type 2 diabetes, but development was halted during phase III clinical trials due to serious hypersensitivity reactions and GI intolerance. It is suspected that the cause of the observed hypersensitivity is due to the presence of amino acid duplication synthesis side product(s) which gives rise to novel T cell epitopes. HLA typing in allergic patients shows an enrichment of five particular HLA DRB1 alleles. Two of these alleles (DRB1*0701 and DRB1*1104) were shown to be able to bind the impurity rather than the drug. Using the WhIM algorithm, we have evaluated all possible amino acid duplication impurities for the presence of new T cell epitopes at both a population level and an individualized level. Out of these possible impurities, five create putative T cell neo-epitopes for the HLA- DR7 and/or DR11 families, and one or more of these could be contributing to the observed hypersensitivity to Taspoglutide in subjects with DRB1*0701 and/or DRB1*1104.
The peptide drug market has rapidly expanded and is expected to generate in excess of $50 billion for manufacturers. While synthetic peptide synthesis is a cost-effective approach for producing these drugs, regulatory agencies are concerned that impurities resulting from the manufacturing process could introduce an unwanted immune response. Impurities can result from changes in the sequences due to deletions, insertions, substitutions, modifications and other impurities related to the synthetic production.
The FDA recently released a new draft guidance defining the equivalence of a rDNA peptide product and a synthetic peptide product enabling generic manufacturers of peptide drugs to file an Abbreviated New Drug Application (ANDA) for synthetic peptide drug products that refer to listed drugs of rDNA origin. Since the processes for manufacturing the generic and reference drug (RLD) are not equivalent, peptide drugs can be associated with impurities. The FDA draft guidance requires manufacturers to prove that synthetic peptide products do not contain impurities that have an increased affinity for major histocompatibility complexes and potential for engaging immune response, which may drive anti-drug antibody development.
Here we describe our PANDA assay that utilizes a combination of in silico assessment tools and in vitro assays to predict and validate the effect of peptide impurities on the immunogenicity of synthetic peptide drug products. In addition, we have developed a novel in-silico tool, the “What-if machine”, that mimics the process of synthetic peptide manufacturing and predicts the impact of impurities at any position in the sequence of a peptide drug.
Step 1. Immunoinformatics assessment: The potential of the DS to stimulate a T cell response can be rapidly assessed computationally using T cell epitope mapping algorithms. We use EpiMatrix for this purpose and focus on HLA DR (Class II) HLA binding predictions. In a typical DS analysis, the EpiMatrix algorithm is used to screen the primary amino acid sequence of the DS and its impurities, for the presence of HLA DR ligands, which can be considered putative T cell epitopes. Discriminating between potential inflammatory “T effector” epitopes and regulatory “T reg” epitopes is performed with a second algorithm, known as JanusMatrix. The latter algorithm identifies putative Treg epitopes, defined as HLA/epitope complexes that present a human-like outer contour (TCR face). HLA/epitope complexes that do not present an outer contour (TCR face) that is ‘human-like’ are more likely to drive effector T cell response. Following assessment of T cell epitope phenotype, the next step is to combine the scores for effector and regulatory T cell epitope content, providing an overall assessment of immunogenic potential of the DS and impurities. The resulting Treg adjusted EpiMatrix scores are highly correlated with immune responses in vivo.
Step 2: In vitro - HLA binding: The DS, its impurities, and peptides representing predicted T cell epitopes can be evaluated for binding to human HLA in assays that measure binding affinity in dose-ranging studies, in vitro. HLA binding is used to confirm in the in silico analysis and inform the design of in vitro assays (see step 3).
Step 3: In vitro assay – Teff Assay: Measurement of de novo T cell response: Cell culture protocols have been developed to emulate in vivo conditions that support differentiation of naïve T cells to effector T cells by antigen stimulation with biologics or their constituent T cell epitopes. In vitro stimulations using the biologic drug and human peripheral blood cells (PBMC) allow for natural antigen processing of the DS and other product components including impurities. In vitro assays using predicted epitopes derived from the DS product impurities provide information about the ability of these defined sequences to drive a T cell response using human T cells. At the end of the culture period, T cell phenotype and/or function are characterized in assays that measure the magnitude and quality of effector T cells that have potential to drive ADA development. Treg Assay: Co-incubation of the putative Treg epitopes with known T effector epitopes (such as Tetanus Toxoid-derived T effector epitopes) allows the assessment of bystander suppression. Bystander suppression is a feature of Treg epitopes.
In summary, in silico and in vitro assessment of novel T effector (inflammatory) and Treg (suppressive) epitopes is necessary to best evaluate the impact of novel impurities on the immunogenicity risk in humans. In addition to the standardized tools described above, we will describe novel in silico methods that have been developed to anticipate well-known synthetic peptide impurities (The What If Machine). A case study of Taspoglutide will be provided to illustrate these well-established (and more recently developed) Immunogenicity Risk Assessment methods.
Peptides are highly active biological molecules that, with advances in stability and delivery, present huge potential as drug candidates. With an increased interest in the use of peptides as therapeutics comes the need for strategies to allow for the discovery of novel hit candidates, in a high throughput manner, from highly complex peptide libraries.
Current technologies for the discovery of novel peptide therapeutics include phage, yeast, ribosomal and mRNA display but these all hold their own limitations. Phage and yeast display are sensitive but a reliance upon a biological host can result in replication bias and interference from native host proteins. These systems are also restricted to the use of natural amino acids. In vitro technologies based on mRNA and ribosomal display have the ability to incorporate unnatural amino acids but are limited by small peptide copy number leading to a reduced detection of low affinity binders. Moreover, none of the current peptide display technologies can effectively address cell surface targets for the discovery of functional peptides.
The ORBIT in vitro display technology uses beads to present randomised peptide sequences and the DNA which encodes them, thereby linking genotype to phenotype, and combines the advantages of in vitro display, such as highly diverse libraries and a cell-free environment, with the high sensitivity of in vivo technologies. The ORBIT display platform presents thousands of identical peptide copies per bead allowing for the discovery of low affinity binders and allows for the incorporation of unnatural amino acids and the generation of cyclic peptides which can increase chemical diversity and improve stability, specificity and affinity. In addition to screening for binding peptides, the ORBIT platform can be adapted to screen whole cell surfaces for peptides which elicit functional cellular responses.
In summary, the ORBIT peptide display platform offers peptide drug screening with high diversity, sensitivity and plasticity, and has the potential to discover novel, selective and functional peptide therapeutic leads with a broad target coverage, including cell surface targets, for a wide range of diseases.
Rationally designed protein domain mimics are based on secondary and tertiary structure epitopes observed at protien-protein interfaces. Successful development relies on interplay between good quality crystal and computational data, with iterative synthesis of scaffolds displaying key residues involved in binding. These direct mimics are limited in their binding affinity by the functional transience and low affinity of the native complex and require significant optimisation. We seek to translate an optimised tertiary mimic scaffold, a crosslinked helical dimer, to a phage screening platform that would allow access to diverse libraries of conformationally defined interfaces. The libraries could then be refined against a target of interest and amplified for further rounds of selection, deviating from the need to define the target epitope by structural analysis. With our developed library, we screened against VEGF, identifying 8 unique sequences which have been shown to bind by ELISA, and in vitro binding studies using fluorescence polarisation are underway.
Daniel Samson
Vice President API Manufacturing, Bachem
Bachem’s modular concept for CMC development is based on experience with a wide range of customers. The concept covers the complete API life cycle and will be discussed with emphasis on milestones and deliverables commensurate to the clinical development phases.
After obtaining his PhD in organic and physical chemistry Daniel joined Bachem's peptide manufacturing headquarters in Switzerland in 2007. As a team leader he has been responsible for the synthesis of peptides and small proteins. From 2009 to 2011 he held a lab head position focusing on process optimization, technology transfer and scale-up of synthetic peptide manufacturing procedures. In 2010 Daniel joined Bachem in the United Kingdom temporarily focusing on non-GMP custom syntheses of peptides. From the beginning of 2012 he has been leading Bachem’s cGMP API manufacturing groups back in Switzerland applying large scale SPPS and preparative HPLC. He is currently a Vice President API Manufacturing and has full responsibility for all solid-phase peptide manufacturing aspects within Bachem AG.
Insulin and its analogs used in the diabetes treatment are often insufficient due to the inability of these exogenous insulins to function in response to the varying glucose concentration and resulting hypoglycemia. A novel approach to improve such narrow therapeutic index by conjugation of a cluster of sugars, e.g., D-mannose and L-fucose, to insulin, has been explored to potentially offer glucose responsive insulins with low hypoglycemia risk. The cluster of sugar moieties, acting as substrate of endogenous mannose receptor (MR), have been shown to affect the pharmacokinetic properties of their corresponding insulin conjugates in a way that is sensitive to the endogenous glucose concentration, rendering these insulin conjugates low risk of hypoglycemia. This presentation will cover our effort in the design and synthesis of insulin oligosaccharide conjugates (IOCs) that showed efficacy in clinically relevant minipig models with /without the presence of α -methyl mannose, a glucose surrogate; and our effort of developing a potent follow-up candidate to our first clinical candidate MK-2640.