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The Digital Patient - How synthetic data can advance medical research
No full textContinuous patient data collection through research and clinical practice in healthcare and drug development has the potential to greatly improve our understanding of disease and treatment. However, patient data are subject to many constraints that can limit how this potential may be realized:
• Consent and data privacy laws limit the purpose for which data may be used or even just moved or processed.
• Data collection is not implemented in the same way across data sources: For example, images may have different resolution or quality across measurements, or patients may have different visit schedules.
• Availability of different data modalities, such as particular measurements or medical images, may vary across patients and datasets.
In this article, we’ll take a quick look at the foundations of Generative Adversarial Networks and then examine some advances we made in creating multi-modal synthesizers which can help us address some of the challenges outlined above. In particular, we will look at creating three-dimensional, high-resolution images and clinical data in one pass, ensuring cross-modal correlation. A big aspect of this project so far was enabling the capability of conditioned synthesis. We’ll look at some example results and talk about potential applications
Mutually Rewarding Academia-Industry Collaborations in the Field of Chemical Biology
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Retinal dystrophy associated with RLBP1 retinitis pigmentosa: A 5-year prospective natural history study
No full textPurpose: To assess the progression in functional and structural measures over a period of 5 years in patients with retinal dystrophy due to RLBP1 gene mutation.
Methods: This prospective, non-interventional study included patients from two clinical sites in Sweden and Canada with biallelic RLBP1 mutations. Key assessments included: ocular examinations; visual functional measures (best corrected visual acuity [BCVA], contrast sensitivity [CS], dark-adaptation [DA] kinetics up to 6 hours for 2 wavelengths [450 and 632 nm], Humphrey visual fields [HVF], full-field flicker electroretinograms [ERG]); and structural ocular assessments.
Results: Of the 45 patients enrolled, 38 completed the full five years of follow-up. At baseline, patients had good vision to severe visual loss, poor CS, HVF defects, and prominent thinning in central foveal thickness. All patients had extremely prolonged DA rod recovery of ~6 hours at both wavelengths. The test-retest repeatability was high across all anatomic and functional endpoints. Cross-sectionally, poorer VA was associated with older age (right eye 0.606, left eye 0.578; p<0.001) and HVF MD values decreased with age (right eye -0.672, left eye -0.654; p<0.001). However, no major changes in functional or structural measures were noted longitudinally over the 5-year period.
Conclusions: This natural history study, which is the first study to follow patients with RLBP1 RD for 5 years, showed that severely delayed DA sensitivity recovery, a characteristic feature of this disease, was observed in all patients across all age groups (17-69 years), making it a potentially suitable efficacy assessment for gene therapy treatment in this patient population
Discovery of the TLR7/8 Antagonist MHV370 for Treatment of Systemic Autoimmune Diseases.
No full textToll-like receptor (TLR) 7 and TLR8 are endosomal sensors of the innate immune system that are activated by GU-rich single stranded RNA (ssRNA). Multiple genetic and functional lines of evidence link chronic activation of TLR7/8 to the pathogenesis of systemic autoimmune diseases (sAID) such as Sjögren's syndrome (SjS) and systemic lupus erythematosus (SLE). This makes targeting TLR7/8-induced inflammation with small-molecule inhibitors an attractive approach for the treatment of patients suffering from systemic autoimmune diseases. Here, we describe how structure-based optimization of compound 2 resulted in the discovery of 34 (MHV370, (S)-N-(4-((5-(1,6-dimethyl-1H-pyrazolo[3,4-b]pyridin-4-yl)-3-methyl-4,5,6,7-tetrahydro-1H-pyrazolo[4,3-c]pyridin-1-yl)methyl)bicyclo[2.2.2]octan-1-yl)morpholine-3-carboxamide). Its in vivo activity allows for further profiling toward clinical trials in patients with autoimmune disorders, and a Phase 2 proof of concept study of MHV370 has been initiated, testing its safety and efficacy in patients with Sjögren's syndrome and mixed connective tissue disease
Acceptable Intakes (AIs) for 11 Simple N-Nitrosamine (NA) Impurities
No full textLow levels of N-nitrosamine (NA) impurities were detected in pharmaceuticals and, as a result, health authorities (HAs) have developed acceptable intakes (AI) as a protective control on the level of NA permissible in pharmaceuticals. Eleven common NA impurities were analyzed in a comprehensive and transparent toxicological process consistent with ICH M7 and compared to the AIs developed by HAs. This comprehensive analysis included substances which had datasets which were robust, limited but sufficient, and substances with insufficient carcinogenicity data. In the case of robust or limited but sufficient carcinogenicity information, AIs were calculated based on published or derived TD50’s from the most sensitive organ site. In the case of insufficient carcinogenicity information, available carcinogenicity data and structure activity relationship (SAR) was used and applied to existing thresholds of 1500 ng/day, 150 ng/day or 18 ng/day. This approach advances the methodology used to derive AIs for NA impurities
A model-informed method to retrieve intrinsic from apparent cooperativity and project cellular target occupancy for ternary complex-forming compounds.
No full textThere is an increasing interest to develop therapeutics that modulate challenging or undruggable target proteins via a mechanism that involves ternary complexes. In general, such compounds can be characterized by their direct affinities to a chaperone and a target protein and by their degree of cooperativity in the formation of the ternary complex. As a trend, smaller compounds have a greater dependency on intrinsic cooperativity to their thermodynamic stability relative to direct target (or chaperone) binding. This highlights the need to consider intrinsic cooperativity of ternary complex-forming compounds early in lead optimization, especially as they provide more control over target selectivity (especially for isoforms) and more insight into the relationship between target occupancy and target response via estimation of ternary complex concentrations. This motivates the need to quantify the natural constant of intrinsic cooperativity (α) which is generally defined as the gain (or loss) in affinity of a compound to its target in pre-bound vs. unbound state. Intrinsic cooperativities can be retrieved via a mathematical binding model from EC50 shifts of binary binding curves of the ternary complex-forming compound with either a target or chaperone relative to the same experiment but in the presence of the counter protein. In this manuscript, we present a mathematical modeling methodology that estimates the intrinsic cooperativity value from experimentally observed apparent cooperativities. This method requires only the two binary binding affinities and the protein concentrations of target and chaperone and is therefore suitable for use in early discovery therapeutic programs. This approach is then extended from biochemical assays to cellular assays (i.e., from a closed system to an open system) by accounting for differences in total ligand vs. free ligand concentrations in the calculations of ternary complex concentrations. Finally, this model is used to translate biochemical potency of ternary complex-forming compounds into expected cellular target occupancy, which could ultimately serve as a way for validation or de-validation of hypothesized biological mechanisms of action
Direct Deamidation Analysis of Intact Adeno-Associated Virus Serotype 9 (AAV9) Capsid Proteins using Reversed-Phase Liquid Chromatography (RPLC)- Tandem Mass Spectrometry (MS) or RPLC-Fluorescence Detector (FLD)
No full textRecombinant adeno-associated viral (AAV) vectors with nonpathogenic nature and ability to provide long-term gene expression have taken center stage as gene delivery vehicles for gene therapy. AAV capsid proteins (VP) are the major components that determine the tissue specificity, immunogenicity, and in vivo transduction performance of the vector. Asparagine deamidation of AAV capsid proteins has been reported to alter vector function, reduce vector stability and potency of AAV gene therapy products. Deamidation of asparagine residue is a common post-translational modification (PTM) of proteins that is readily detected and quantified by liquid chromatography-tandem mass spectrometry (LC-MS)-based peptide mapping. However, artificial deamidation can be spontaneously induced during sample preparation for peptide mapping prior to LC-MS analysis. We have developed an optimized sample preparation method to reduce and minimize deamidation artifacts induced during sample preparation for peptide mapping, which typically takes several hours to complete. To shorten turnaround time of deamidation results and to avoid artificial deamidation, we developed orthogonal RPLC-MS and RPLC-fluorescence detection (FLD) methods for direct deamidation analysis at the intact AAV9 capsid protein level to routinely support downstream purification, formulation development, and stability testing. Similar trends of increasing deamidation of AAV9 capsid proteins in stability samples were observed at the intact protein level and peptide level, indicating that the developed direct deamidation analysis of intact AAV9 capsid protein is comparable to the peptide mapping-based deamidation analysis and both methods are suitable/alternative for deamidation monitoring of AAV9 capsid proteins
MELLODDY: Cross-pharma Federated Learning at Unprecedented Scale Unlocks Benefits in QSAR without Compromising Proprietary Information.
No full textFederated multipartner machine learning has been touted as an appealing and efficient method to increase the effective training data volume and thereby the predictivity of models, particularly when the generation of training data is resource-intensive. In the landmark MELLODDY project, indeed, each of ten pharmaceutical companies realized aggregated improvements on its own classification or regression models through federated learning. To this end, they leveraged a novel implementation extending multitask learning across partners, on a platform audited for privacy and security. The experiments involved an unprecedented cross-pharma data set of 2.6+ billion confidential experimental activity data points, documenting 21+ million physical small molecules and 40+ thousand assays in on-target and secondary pharmacodynamics and pharmacokinetics. Appropriate complementary metrics were developed to evaluate the predictive performance in the federated setting. In addition to predictive performance increases in labeled space, the results point toward an extended applicability domain in federated learning. Increases in collective training data volume, including by means of auxiliary data resulting from single concentration high-throughput and imaging assays, continued to boost predictive performance, albeit with a saturating return. Markedly higher improvements were observed for the pharmacokinetics and safety panel assay-based task subsets
A Phospho-harmonic Orchestra Plays the NLRP3 Score
No full textNLRP3 is a prototypical sensor protein connecting cellular stress to pro-inflammatory signaling. A complex array of regulatory steps is required to switch NLRP3 from an inactive state into a primed entity that is poised to assemble an inflammasome. Accumulating evidence suggests that post-translational mechanisms are critical. In particular, phosphorylation/dephosphorylation and ubiquitylation/deubiquitylation reactions have been reported to regulate NLRP3. Taken individually, several post-translational modifications appear to be essential. However, it remains difficult to understand how they may be coordinated, whether there is a unique sequence of regulatory steps accounting for the functional maturation of NLRP3, or whether the sequence is subject to variations depending on cell type, the stimulus, and other parameters such as the cellular context.
This review will focus on the regulation of the NLRP3 inflammasome by phosphorylation and dephosphorylation, and on kinases and phosphatases that have been reported to modulate NLRP3 activity. The aim is to try to integrate the current understanding and highlight potential gaps for further studies
Crystal Structures of Inhibitor-Bound Main Protease from Delta- and Gamma-Coronaviruses.
No full textWith the spread of SARS-CoV-2 throughout the globe causing the COVID-19 pandemic, the threat of zoonotic transmissions of coronaviruses (CoV) has become even more evident. As human infections have been caused by alpha- and beta-CoVs, structural characterization and inhibitor design mostly focused on these two genera. However, viruses from the delta and gamma genera also infect mammals and pose a potential zoonotic transmission threat. Here, we determined the inhibitor-bound crystal structures of the main protease (Mpro) from the delta-CoV porcine HKU15 and gamma-CoV SW1 from the beluga whale. A comparison with the apo structure of SW1 Mpro, which is also presented here, enabled the identification of structural arrangements upon inhibitor binding at the active site. The cocrystal structures reveal binding modes and interactions of two covalent inhibitors, PF-00835231 (active form of lufotrelvir) bound to HKU15, and GC376 bound to SW1 Mpro. These structures may be leveraged to target diverse coronaviruses and toward the structure-based design of pan-CoV inhibitors