November'23 Edition
Leveraging Single-Cell RNA Sequencing and AI to Forecast Neuronal Regeneration
Single-cell RNA sequencing and machine learning were used in conjunction to develop a classifier that predicts a neuron's potential to regenerate after an injury based on gene expression data.?
Single-cell RNA sequencing (scRNA) is a technique that studies the gene expression profile of a single cell from a population of cells. This technique captures gene expression variations within an individual cell whereas bulk sequencing of RNA/DNA, studies gene expression variations in tissue/organ level. Hence scRNA is able to provide a deeper understanding of the problem genes and biomarkers. It was in 2009 in their paper titled “mRNA-Seq whole-transcriptome analysis of a single cell †that Tang and his group first described the technical and conceptual breakthrough of single-cell RNA sequencing through sequencing of the transcriptome of a single blastomere and oocyte. From then till now, this technique has enabled researchers to bring to light remarkable discoveries, one of the recent ones being the Regeneration Classifier.
Neurons, the main group of cells that make up the central nervous system, are considered one of the slowest cells to regenerate after an injury. Scientists are still unsure of why certain neurons regenerate while others don't even though a significant understanding of the mechanism of neuronal regeneration has been divulged. To study this heterogeneity, a study by researchers at the University of California San Diego School of Medicine induced neurons from mice with spinal cord injury to regenerate using established molecular techniques after which they were extracted and subjected to single-cell RNA sequencing.
Supervised clustering of single-cell seq data generated a pattern of unique gene expressions that made up the prediction tool the researchers termed the Regeneration Classifier. The Regeneration Classifier grouped the neurons based on their gene expression into one of the following four classes: regenerator, non-regenerator, unknown, and cluster 2. The model validated on 26 published single-cell RNA sequencing datasets of neurons at various developmental stages and of various niches of the nervous system were able to successfully reproduce the actual regeneration potential of the neurons albeit with a few exceptions. Even with the astounding success, the researchers caution against using the model for clinical purposes as it has yet to reach its prime but promotes its use in advancing in the field of neuronal regeneration.
To read more on the study: Deep scRNA sequencing reveals a broadly applicable Regeneration Classifier and implicates antioxidant response in corticospinal axon regeneration
BoltBio is a target discovery in Boltzmann's AI drug discovery suite that analyzes and detects patterns within multi-omics data. It fuses data analytics strategies with the intelligence of AI to discover novel biomarkers and disease targets.
New Antibody Treatment For Alzheimer's Takes Center Stage
US FDA approves the treatment of Alzheimer's disease with Leqembi, which has been listed as one of the best inventions of TIME 2023.?
On June 9, 2023, the FDA's Peripheral and Central Nervous System Drugs (PCNS) advisory committee made a unanimous decision regarding Eisai's Clarity AD clinical trial. They voted to confirm that the data from this trial provided clear evidence of the clinical benefit of LEQEMBI for the treatment of Alzheimer's disease (AD). Additionally, the committee members affirmed that the overall risk-benefit profile of LEQEMBI is favorable, marking a significant step in the potential approval and use of the drug for AD treatment.
Amyloid beta plaques, they are often referred to simply as amyloid plaques, are abnormal protein aggregates that can accumulate in the brains of individuals with Alzheimer's disease. These plaques are the known hallmark of pathological features of the disease and play a significant role in its progression. The probability of having plaques in the brain increases with advancing age. From the age of 60 years to the age of 80 years, the proportion of people with senile plaques increases linearly over time. Women are more prone to have plaques than men.
Lecanemab, marketed under the brand name Leqembi, is an important monoclonal antibody medication specifically designed for the treatment of Alzheimer's disease. It belongs to the class of drugs known as amyloid beta-directed antibodies, which target the accumulation of amyloid beta protein in the brain, a characteristic feature of Alzheimer's disease. Lecanemab is administered through intravenous infusion.
Protein engineering is the scientific process of creating beneficial or valuable proteins such as antibodies by designing and producing unnatural polypeptides This often involves the alteration of amino acid sequences that are naturally occurring in proteins found in living organisms. This field of study has significant applications in biotechnology, drug discovery, and other industries.
BoltPro is an innovative product developed by Boltzmann Labs, designed to revolutionize the manufacturing of antibodies. This cutting-edge technology offers a rapid and cost-effective solution for producing antibodies, significantly reducing both production time and expenses.
“The full, traditional approval of LEQEMBI in the US, combined with the broad Medicare reimbursement, is a paradigm-shifting step in the fight against Alzheimer’s diseaseâ€
-Gunilla Osswald, CEO of BioArctic.
Lupin's Generic Drug Receives FDA Stamp of Approval
Lupin received the FDA’s approval to market generic Fluconazole tablets equivalent to Pfizer’s Diflucan Tablets at 50 mg, 100 mg, 150 mg, and 200 mg.?
Fluconazole is a first-generation triazole antifungal agent that interferes with the ergosterol synthesis, a significant component in the fungal membrane, leaving the organism vulnerable to osmotic and immune-mediated damage while jeopardizing its cell adherence capabilities. The triazole ring of the drug binds with high specificity to the cytochrome P450-dependent 14-α-sterol demethylase enzyme that is responsible for the ergosterol synthesis setting in motion the series of events leading to inhibition of the fungal growth. It has been approved by the FDA for the treatment of both systemic and superficial fungal infections from vaginal, oropharyngeal, and esophageal candidiasis, systemic Candida infections, and peritonitis to name a few.?
Fluconazole emerged as a candidate antifungal agent as far back as in the early 1990s from a study by Dr.Ken Richardson and his team. In 1981 it was patented by Pfizer and was given a fast-track designation. In only 9 months the drug entered the commercial market in 1988 and has then become one of the most used antifungal agents decreasing candidiasis incidence in those with weakened immune systems such as transplant, chemotherapy, and AIDS patients as well as burn victims. Pfizer’s Fluconazole tablets marketed under the brand name Diflucan have an estimated 43 million USD annually. Pfizer's US patent 4404216 for Fluconazole expired as of July 3, 2005 evening the playground for cheaper, generic versions of the drug that can reach a wider population.
On 23rd October 2023, Global pharma major Lupin Limited declared themselves as the newest entry into the fluconazole market gaining the FDA’s? Abbreviated New Drug Application (ANDA) for marketing of Fluconazole Tablets USP, 50 mg, 100 mg, 150 mg, and 200 mg.? The ANDA is a regulatory submission to the FDA for the marketing of a generic drug. It allows the manufacturers to omit extensive clinical testing by showing that their product is bioequivalent to the original brand-name drug. The generic version of Pfizer’s Diflucan will be manufactured in the company’s Pithampur facility in India.
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From target identification to drug design to virtual screening to predicting resistance, AI has made strides in the discovery of new antimicrobials while also significantly reducing the time and cost involved. Boltzmann’s AI-powered small molecule design studio, Boltchem, hosts an array of modules and tools that assist in the complete drug discovery pipeline. Its interface leverages the potential of AI to design/screen novel scaffolds of molecules for a given target protein. The molecules can then be further progressed in ReBolt, an AI-assisted tool for synthesis planning that recommends synthesis pathways of molecules from the ground up listing the byproducts and intermediates steps and links to purchase the reagents and starting materials. It allows the user to make decisions on pathways to be followed on multiple fronts whether that be the availability of starting materials, the expenses, or the resources involved.? Boltchem and ReBolt work seamlessly together to bring novel first-in-class and best-in-class drug molecules into the market.
Key Highlights from CPhI 2023: A Global Pharmaceutical Showcase
The global pharma event, CPHI 2023 took place in Barcelona, Spain on October 24th-26th bringing together the pharma sector for 3 days of discussions, networking, and forecasting on future trends in pharma.
The Convention on Pharmaceutical Ingredients (CPHI) was established in 1990 to bring together professionals from all the niches of the pharmaceutical industry from manufacturers of pharmaceutical ingredients, machinery, and packaging to suppliers to R&D professionals to industry veterans, regulatory experts, consultants, and service providers. It allows the attendees to meet potential clients, understand market trends, showcase their products and solutions, and keep up to date with the shifts in the industry. CPHI provides a global platform to deepen connections to do better business within the pharmaceutical industry.
The CPHI 2023 conducted in Barcelona, Spain discussions revolved around 3 main topics:
- Escalating role of AI?
- India rising to the top in delivering AI-powered innovations in pharma
- Boom of Contract Development and Manufacturing Organizations
This year’s CPHI survey reports AI technologies in drug discovery as the most appealing investment in the pharma industry with 42% of the executives predicting an AI-designed drug to enter the market by 2026. AI’s influence is seeping into multiple industry divisions such as the development of druggable targets, drug discovery, manufacturing, clinical trials, and marketing dossiers. India, with its extensive power in IT and the most extensive base of naive patients in the world for clinical trials, is predicted to be at the forefront of the revolution with the next 5 years expected to witness the fastest growth in biologicals. CPHI also reports the rapid evolution of Contract Development and Manufacturing Organizations (CDMOs) in the Asia-Pacific region, with special emphasis on India as the growth is on par with the predictions of its rising prowess in AI-powered pharma.
To read more: CPHI Annual Report.pdf
?The report states that the industry has shifted back to its pre-pandemic growth drivers in the past year where India’s projected growth rate is expected to rise above that of China’s. Boltzmann Labs, an Indian startup brings into the market a suite of AI-powered tools that accelerates drug discovery on multiple fronts.
RNA Transcriptomics Trends 2023-2032: An Investment Surge
The Global RNA Transcriptomics Market experienced substantial growth, rising from $5.96 billion in 2022 to $6.76 billion in 2023, representing a notable Compound Annual Growth Rate (CAGR) of 13.4%. The Transcriptomics Technologies Market is expected to continue its upward trajectory, with an anticipated value of USD 7,708.5 million by 2028, growing at a CAGR of 9.0%, and it is set to reach a substantial value of USD 20.75 billion in 2032.
The rapid expansion of the transcriptomics market can be attributed to the surging research activities in personalized medicine, next-generation sequencing (NGS), CRISPR-Cas9, biomedical research, and a notable increase in funding and investments.???
Market Insights:
Next-generation sequencing (NGS) methods in transcriptomics, such as RNA sequencing, are transformative tools that revolutionize the study of gene expression, alternative splicing, and non-coding RNA regulation. They enable comprehensive insights into gene expression patterns and isoform diversity, enhancing our understanding of cellular processes and also aid in reconstructing and annotating the transcriptome, identifying novel transcripts and regulatory elements. NGS supports the emergence of single-cell transcriptomics, revealing cellular heterogeneity and gene expression dynamics
There has been substantial growth in spatial transcriptomics techniques, which offer researchers the ability to investigate gene expression patterns at both the individual cell and tissue levels across a range of disciplines. Among the widely adopted methods are ST/Visium, Nanostring DSP, LCM, and Tomo-seq, while MERFISH and ISS2 find popularity for targeted investigations. ISS and smFISH-based approaches facilitate single-cell analysis of specific genes, whereas transcriptome-wide and de novo studies can be achieved through capture and dissociation methods. The global spatial genomics transcriptomics market was assessed to be worth approximately US$ 262.7 million in 2023 and is anticipated to achieve a value of about US$ 618.9 million by 2030, exhibiting a compounded annual growth rate (CAGR) of 13% between 2023 and 2030.
To Read More: https://www.coherentmarketinsights.com/market-insight/spatial-genomics-transcriptomics-market-6142
AI-driven advancements in transcriptomics are revolutionizing data extraction from bulk RNA-seq data. These methods find wide application across gene expression, splicing, transcription factors, and cell deconvolution, propelling the field's development. Cutting-edge bioinformatics frameworks, leveraging AI algorithms like RF, SVM, and CNN, drive specific tasks such as trajectory inference and batch effect removal, underscoring AI's pivotal role in enhancing our understanding of transcriptomics.???
Emerging technologies, such as NGS and CRISPR-Cas9 gene editing, have brought about a transformative impact on RNA analysis. These innovations have enhanced the efficiency and precision of gene expression pattern studies. Furthermore, the rising utilization of cloud-based solutions for data management and analysis is projected to drive market expansion. The increased investments in RNA research, spanning governmental, academic, and private sectors, are fostering collaboration and innovation in RNA-based products and technologies. This comprehensive investment surge is propelling the field forward.
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