Digital pathology for reporting histopathology samples, including cancer screening samples - definitive evidence from a multisite study.

AIMS: To conduct a definitive multicentre comparison of digital pathology (DP) with light microscopy (LM) for reporting histopathology slides including breast and bowel cancer screening samples. METHODS: A total of 2024 cases (608 breast, 607 GI, 609 skin, 200 renal) were studied, including 207 breast and 250 bowel cancer screening samples. Cases were examined by four pathologists (16 study pathologists across the four speciality groups), using both LM and DP, with the order randomly assigned and 6 weeks between viewings. Reports were compared for clinical management concordance (CMC), meaning identical diagnoses plus differences which do not affect patient management. Percentage CMCs were computed using logistic regression models with crossed random-effects terms for case and pathologist. The obtained percentage CMCs were referenced to 98.3% calculated from previous studies. RESULTS: For all cases LM versus DP comparisons showed the CMC rates were 99.95% [95% confidence interval (CI) = 99.90-99.97] and 98.96 (95% CI = 98.42-99.32) for cancer screening samples. In speciality groups CMC for LM versus DP showed: breast 99.40% (99.06-99.62) overall and 96.27% (94.63-97.43) for cancer screening samples; [gastrointestinal (GI) = 99.96% (99.89-99.99)] overall and 99.93% (99.68-99.98) for bowel cancer screening samples; skin 99.99% (99.92-100.0); renal 99.99% (99.57-100.0). Analysis of clinically significant differences revealed discrepancies in areas where interobserver variability is known to be high, in reads performed with both modalities and without apparent trends to either. CONCLUSIONS: Comparing LM and DP CMC, overall rates exceed the reference 98.3%, providing compelling evidence that pathologists provide equivalent results for both routine and cancer screening samples irrespective of the modality used.

Diastereoselectivity is in the Details: Minor Changes Yield Major Improvements to the Synthesis of Bedaquiline.

Bedaquiline is a crucial medicine in the global fight against tuberculosis, yet its high price places it out of reach for many patients. Herein, we describe improvements to the key industrial lithiation-addition sequence that enable a higher yielding and therefore more economical synthesis of bedaquiline. Prioritization of mechanistic understanding and multi-lab reproducibility led to optimized reaction conditions that feature an unusual base-salt pairing and afford a doubling of the yield of racemic bedaquiline. We anticipate that implementation of these improvements on manufacturing scale will be facile, thereby substantially increasing the accessibility of this essential medication.

Artificial intelligence for advance requesting of immunohistochemistry in diagnostically uncertain prostate biopsies.

The use of immunohistochemistry in the reporting of prostate biopsies is an important adjunct when the diagnosis is not definite on haematoxylin and eosin (H&E) morphology alone. The process is however inherently inefficient with delays while waiting for pathologist review to make the request and duplicated effort reviewing a case more than once. In this study, we aimed to capture the workflow implications of immunohistochemistry requests and demonstrate a novel artificial intelligence tool to identify cases in which immunohistochemistry (IHC) is required and generate an automated request. We conducted audits of the workflow for prostate biopsies in order to understand the potential implications of automated immunohistochemistry requesting and collected prospective cases to train a deep neural network algorithm to detect tissue regions that presented ambiguous morphology on whole slide images. These ambiguous foci were selected on the basis of the pathologist requesting immunohistochemistry to aid diagnosis. A gradient boosted trees classifier was then used to make a slide-level prediction based on the outputs of the neural network prediction. The algorithm was trained on annotations of 219 immunohistochemistry-requested and 80 control images, and tested by threefold cross-validation. Validation was conducted on a separate validation dataset of 222 images. Non IHC-requested cases were diagnosed in 17.9 min on average, while IHC-requested cases took 33.4 min over multiple reporting sessions. We estimated 11 min could be saved on average per case by automated IHC requesting, by removing duplication of effort. The tool attained 99% accuracy and 0.99 Area Under the Curve (AUC) on the test data. In the validation, the average agreement with pathologists was 0.81, with a mean AUC of 0.80. We demonstrate the proof-of-principle that an AI tool making automated immunohistochemistry requests could create a significantly leaner workflow and result in pathologist time savings.

A High-Yielding Synthesis of EIDD-2801 from Uridine.

A simple reordering of the reaction sequence allowed the improved synthesis of EIDD-2801, an antiviral drug with promising activity against the SARS-CoV-2 virus, starting from uridine. Compared to the original route, the yield was enhanced from 17 % to 61 %, and fewer isolation/purification steps were needed. In addition, a continuous flow procedure for the final acetonide deprotection was developed, which proved to be favorable toward selectivity and reproducibility.

Validation of digital pathology imaging for primary histopathological diagnosis.

AIMS: Digital pathology (DP) offers advantages over glass slide microscopy (GS), but data demonstrating a statistically valid equivalent (i.e. non-inferior) performance of DP against GS are required to permit its use in diagnosis. The aim of this study is to provide evidence of non-inferiority. METHODS AND RESULTS: Seventeen pathologists re-reported 3017 cases by DP. Of these, 1009 were re-reported by the same pathologist, and 2008 by a different pathologist. Re-examination of 10 138 scanned slides (2.22 terabytes) produced 72 variances between GS and DP reports, including 21 clinically significant variances. Ground truth lay with GS in 12 cases and with DP in nine cases. These results are within the 95% confidence interval for existing intraobserver and interobserver variability, proving that DP is non-inferior to GS. In three cases, the digital platform was deemed to be responsible for the variance, including a gastric biopsy, where Helicobacter pylori only became visible on slides scanned at the ×60 setting, and a bronchial biopsy and penile biopsy, where dysplasia was reported on DP but was not present on GS. CONCLUSIONS: This is one of the largest studies proving that DP is equivalent to GS for the diagnosis of histopathology specimens. Error rates are similar in both platforms, although some problems e.g. detection of bacteria, are predictable.

A three-minute synthesis and purification of ibuprofen: pushing the limits of continuous-flow processing.

In a total residence time of three minutes, ibuprofen was assembled from its elementary building blocks with an average yield of above 90% for each step. A scale-up of this five-stage process (3 bond-forming steps, one work-up, and one in-line liquid-liquid separation) provided ibuprofen at a rate of 8.09 g h(-1) (equivalent to 70.8 kg y(-1)) using a system with an overall footprint of half the size of a standard laboratory fume hood. Aside from the high throughput, several other aspects of this synthesis expand the capabilities of continuous-flow processing, including a Friedel-Crafts acylation run under neat conditions and promoted by AlCl3, an exothermic in-line quench of high concentrations of precipitation-prone AlCl3, liquid-liquid separations run at or above 200 psi to provide solvent-free product, and the use of highly aggressive oxidants, such as iodine monochloride. The use of simple, inexpensive, and readily available reagents thus affords a practical synthesis of this important generic pharmaceutical.

BAI3, CDX2 and VIL1: a panel of three antibodies to distinguish small cell from large cell neuroendocrine lung carcinomas.

AIMS: Discriminating small-cell lung carcinoma (SCLC) from large-cell neuroendocrine carcinoma (LCNEC) rests on morphological criteria, and reproducibility has been shown to be poor. We aimed to identify immunohistochemical markers to assist this diagnosis. METHODS AND RESULTS: Gene expression profiling on laser captured frozen tumour samples from eight SCLC and eight LCNEC tumours identified a total of 888 differentially expressed genes (DEGs), 23 of which were validated by qRT-PCR. Antibodies to four selected gene products were then evaluated as immunohistochemical markers on a cohort of 173 formalin-fixed paraffin-embedded (FFPE) SCLC/LCNEC tumour samples, including 26 indeterminate tumours without a consensus diagnosis. Three markers, CDX2, VIL1 and BAI3, gave significantly different results in the two tumour types (P < 0.0001): CDX2 and VIL1 in combination (either marker positive) showed sensitivity and specificity of 81% for LCNEC while BAI3 showed 89% sensitivity and 75% specificity for SCLC. Of the 26 indeterminate tumours 15 (58%) showed an immunophenotype suggesting either SCLC or LCNEC, eight (31%) showed staining of both tumour types, and three (11%) were negative for all markers. CONCLUSION: A panel of three markers, BAI3, CDX2 and VIL1, is a useful adjunct in the diagnosis of these tumour types.

Using Systemised Nomenclature of Medicine (SNOMED) codes to select digital pathology whole slide images for long-term archiving.

The archiving of whole slide images represents a hurdle to digital pathology implementation largely because of the amount of data generated. The retention of glass slides is currently recommended for a minimum of 10 years, but it is for individual departments to determine how digital images are archived and for how long. In a retrospective study, we examined the combination of Systemised Nomenclature of Medicine (SNOMED) codes allocated to cases reported between July 2011 and December 2015 and recalled more than 12 months after diagnosis in comparison to non-recalled cases.Our results show that 0.2% of cases are recalled after 12 months, and SNOMED code combinations can be used to identify which cases are likely to be recalled and which are not. This approach could reduce the number of cases archived by 62% and still ensure all cases likely to be recalled remain in the archive.

Short and Efficient Synthesis of the Antituberculosis Agent Pretomanid from (R)-Glycidol.

An efficient gram-scale synthesis of the antituberculosis agent pretomanid using straightforward chemistry, mild reaction conditions, and readily available starting materials is reported. Four different protecting groups on the glycidol moiety were investigated for their technical feasibility and ability to suppress side reactions. Starting from readily available protected (R)-glycidols and 2-bromo-4-nitro-1H-imidazole, pretomanid could be prepared in a linear three-step synthesis in up to 40% isolated yield. In contrast to most syntheses reported so far, deprotection and cyclization were performed in a one-pot fashion without any hazardous steps or starting materials.

Technical note on the exploration of COVID-19 in autopsy material.

Interrogation of immune response in autopsy material from patients with SARS-CoV-2 is potentially significant. We aim to describe a validated protocol for the exploration of the molecular physiopathology of SARS-CoV-2 pulmonary disease using multiplex immunofluorescence (mIF).The application of validated assays for the detection of SARS-CoV-2 in tissues, originally developed in our laboratory in the context of oncology, was used to map the topography and complexity of the adaptive immune response at protein and mRNA levels.SARS-CoV-2 is detectable in situ by protein or mRNA, with a sensitivity that could be in part related to disease stage. In formalin-fixed, paraffin-embedded pneumonia material, multiplex immunofluorescent panels are robust, reliable and quantifiable and can detect topographic variations in inflammation related to pathological processes.Clinical autopsies have relevance in understanding diseases of unknown/complex pathophysiology. In particular, autopsy materials are suitable for the detection of SARS-CoV-2 and for the topographic description of the complex tissue-based immune response using mIF.

Practical and Scalable Two-Step Process for 6-(2-Fluoro-4-nitrophenyl)-2-oxa-6-azaspiro[3.3]heptane: A Key Intermediate of the Potent Antibiotic Drug Candidate TBI-223.

A low-cost, protecting group-free route to 6-(2-fluoro-4-nitrophenyl)-2-oxa-6-azaspiro[3.3]heptane (1), the starting material for the in-development tuberculosis treatment TBI-223, is described. The key bond forming step in this route is the creation of the azetidine ring through a hydroxide-facilitated alkylation of 2-fluoro-4-nitroaniline (2) with 3,3-bis(bromomethyl)oxetane (BBMO, 3). After optimization, this ring formation reaction was demonstrated at 100 g scale with isolated yield of 87% and final product purity of >99%. The alkylating agent 3 was synthesized using an optimized procedure that starts from tribromoneopentyl alcohol (TBNPA, 4), a commercially available flame retardant. Treatment of 4 with sodium hydroxide under Schotten-Baumann conditions closed the oxetane ring, and after distillation, 3 was recovered in 72% yield and >95% purity. This new approach to compound 1 avoids the previous drawbacks associated with the synthesis of 2-oxa-6-azaspiro[3,3]heptane (5), the major cost driver used in previous routes to TBI-223. The optimization and multigram scale-up results for this new route are reported herein.

Developing an atroposelective dynamic kinetic resolution of MRTX1719 by resolving incompatible chemical operations.

A high-yielding protocol for atropisomeric resolution was developed by rectifying incompatibilities between crystallization and epimerization via continuous processing. Application toward synthesis of MRTX1719, a densely functionalized active pharmaceutical ingredient (API), improved yield from 37% to 87%. This protocol provides a complementary means to access rotamers which challenge current asymmetric methodologies, and greatly improves sustainability by decreasing the consumption of solvent and advanced synthetic intermediates.

Lessons from a breast cell annotation competition series for school pupils.

Due to COVID-19 outbreaks, most school pupils have had to be home-schooled for long periods of time. Two editions of a web-based competition "Beat the Pathologists" for school age participants in the UK ran to fill up pupils' spare time after home-schooling and evaluate their ability on contributing to AI annotation. The two editions asked the participants to annotate different types of cells on Ki67 stained breast cancer images. The Main competition was at four levels with different level of complexity. We obtained annotations of four kinds of cells entered by school pupils and ground truth from expert pathologists. In this paper, we analyse school pupils' performance on differentiating different kinds of cells and compare their performance with two neural networks (AlexNet and VGG16). It was observed that children tend to get very good performance in tumour cell annotation with the best F1 measure 0.81 which is a metrics taking both false positives and false negatives into account. Low accuracy was achieved with F1 score 0.75 on positive non-tumour cells and 0.59 on negative non-tumour cells. Superior performance on non-tumour cell detection was achieved by neural networks. VGG16 with training from scratch achieved an F1 score over 0.70 in all cell categories and 0.92 in tumour cell detection. We conclude that non-experts like school pupils have the potential to contribute to large-scale labelling for AI algorithm development if sufficient training activities are organised. We hope that competitions like this can promote public interest in pathology and encourage participation by more non-experts for annotation.

Facile and Scalable Methodology for the Pyrrolo[2,1-f][1,2,4]triazine of Remdesivir.

Pyrrolo[2,1-f][1,2,4]triazine (1) is an important regulatory starting material in the production of the antiviral drug remdesivir. Compound 1 was produced through a newly developed synthetic methodology utilizing simple building blocks such as pyrrole, chloramine, and formamidine acetate by examining the mechanistic pathway for the process optimization exercise. Triazine 1 was obtained in 55% overall yield in a two-vessel-operated process. This work describes the safety of the process, impurity profiles and control, and efforts toward the scale-up of triazine for the preparation of kilogram quantity.

Development of a Practical Synthesis of the 8-FDC Fragment of OPC-167832.

A concise and practical synthesis has been developed to provide the 8-fluoro-5-hydroxy-3,4-diydrocarbostyril (8-FDC) fragment of OPC-167832 in 41% yield and in >99% purity over four steps from 3-amino-4-fluorophenol. The key feature of this process is the development of a telescoped one-pot synthesis of the quinolone via a chemoselective amidation/acid-induced cyclization that allows for simple product isolation without the need for column chromatography.

Diagnostic concordance and discordance in digital pathology: a systematic review and meta-analysis.

BACKGROUND: Digital pathology (DP) has the potential to fundamentally change the way that histopathology is practised, by streamlining the workflow, increasing efficiency, improving diagnostic accuracy and facilitating the platform for implementation of artificial intelligence-based computer-assisted diagnostics. Although the barriers to wider adoption of DP have been multifactorial, limited evidence of reliability has been a significant contributor. A meta-analysis to demonstrate the combined accuracy and reliability of DP is still lacking in the literature. OBJECTIVES: We aimed to review the published literature on the diagnostic use of DP and to synthesise a statistically pooled evidence on safety and reliability of DP for routine diagnosis (primary and secondary) in the context of validation process. METHODS: A comprehensive literature search was conducted through PubMed, Medline, EMBASE, Cochrane Library and Google Scholar for studies published between 2013 and August 2019. The search protocol identified all studies comparing DP with light microscopy (LM) reporting for diagnostic purposes, predominantly including H&E-stained slides. Random-effects meta-analysis was used to pool evidence from the studies. RESULTS: Twenty-five studies were deemed eligible to be included in the review which examined a total of 10 410 histology samples (average sample size 176). For overall concordance (clinical concordance), the agreement percentage was 98.3% (95% CI 97.4 to 98.9) across 24 studies. A total of 546 major discordances were reported across 25 studies. Over half (57%) of these were related to assessment of nuclear atypia, grading of dysplasia and malignancy. These were followed by challenging diagnoses (26%) and identification of small objects (16%). CONCLUSION: The results of this meta-analysis indicate equivalent performance of DP in comparison with LM for routine diagnosis. Furthermore, the results provide valuable information concerning the areas of diagnostic discrepancy which may warrant particular attention in the transition to DP.

Digital pathology and artificial intelligence will be key to supporting clinical and academic cellular pathology through COVID-19 and future crises: the PathLAKE consortium perspective.

The measures to control the COVID-19 outbreak will likely remain a feature of our working lives until a suitable vaccine or treatment is found. The pandemic has had a substantial impact on clinical services, including cancer pathways. Pathologists are working remotely in many circumstances to protect themselves, colleagues, family members and the delivery of clinical services. The effects of COVID-19 on research and clinical trials have also been significant with changes to protocols, suspensions of studies and redeployment of resources to COVID-19. In this article, we explore the specific impact of COVID-19 on clinical and academic pathology and explore how digital pathology and artificial intelligence can play a key role to safeguarding clinical services and pathology-based research in the current climate and in the future.

Progress Toward a Large-Scale Synthesis of Molnupiravir (MK-4482, EIDD-2801) from Cytidine.

Molnupiravir (MK-4482, EIDD-2801) is a promising orally bioavailable drug candidate for the treatment of COVID-19. Herein, we describe a supply-centered and chromatography-free synthesis of molnupiravir from cytidine, consisting of two steps: a selective enzymatic acylation followed by transamination to yield the final drug product. Both steps have been successfully performed on a decagram scale: the first step at 200 g and the second step at 80 g. Overall, molnupiravir has been obtained in a 41% overall isolated yield compared to a maximum 17% isolated yield in the patented route. This route provides many advantages to the initial route described in the patent literature and would decrease the cost of this pharmaceutical should it prove safe and efficacious in ongoing clinical trials.

Application of Vinamidinium Salt Chemistry for a Palladium Free Synthesis of Anti-Malarial MMV048: A "Bottom-Up" Approach.

MMV390048 (1) is a clinical compound under investigation for antimalarial activity. A new synthetic route was developed which couples two aromatic fragments while forming the central pyridine ring over two steps. This sequence takes advantage of raw materials used in the existing etoricoxib supply chain and eliminates the need for palladium catalysts, which were projected to be major cost-drivers.

Toward a Practical, Nonenzymatic Process for Investigational COVID-19 Antiviral Molnupiravir from Cytidine: Supply-Centered Synthesis.

A scalable four-step synthesis of molnupiravir from cytidine is described herein. The attractiveness of this approach is its fully chemical nature involving inexpensive reagents and more environmentally friendly solvents such as water, isopropanol, acetonitrile, and acetone. Isolation and purification procedures are improved in comparison to our earlier study as all intermediates can be isolated via recrystallization. The key steps in the synthesis, namely, ester formation, hydroxyamination, and deprotection were carried out on a multigram scale to afford molnupiravir in 36-41% yield with an average purity of 98 wt % by qNMR and 99 area% by HPLC.