With the passage of the US Senate by the end of September 2022, the FDA Modernization Act, drug developers have the opportunity to set a historic precedent by abandoning animal models in preclinical development. The bill clearly proposes to reduce animal experiments. On the one hand, it may temporarily escape the death of millions of experimental animals in the laboratory Thriving in an increasingly technologically complex world.
At the forum “A New Revolution in Drug Discovery: Big Data Innovation and Artificial Intelligence” held on November 9, Dr Quin Wills, Ocher Bio’s chief scientific officer, spoke about how the company is developing computer and human preclinical models Making contributions to stimulate innovation in biotechnology.
In addition to discussions regarding artificial intelligence and big data, Dr. Lin Yanzhu, CEO of Insilico Medicine Taiwan, spoke about how its artificial intelligence platform can help accelerate the development of drug treatments. Professor Liao Zhongqi, CEO of Syncell, talked about the company’s new optoproteomics platform and its potential application in the drug discovery process. Dr. Inca Chen, R&D Manager of Acer Value Innovation Center, emphasized the role of artificial intelligence in the future and next generation progression in personalized immuno-oncology therapy.
Biomedical Industry Needs to Avoid Animal Models
For more than a hundred years, the first step in drug development has been to use mammalian models to predict the efficacy and safety of test drugs in humans. Although scientists have developed hundreds of treatments through animal experiments, with the development of technology and human understanding of complex biological processes, animal models may not be able to meet the needs of developing a new generation of treatments.
Today, Ocher Biomedical is leading the development of revolutionary preclinical models to create more effective therapies at an unprecedented rate. Dr Quin Wills said the company uses computer models to study liver disease and has generated a large amount of data to identify the complex links between biological processes and help identify more effective therapeutic targets.
Dr. emphasized. Wills that one reason for the greater benefit of studying human tissue directly than animal tissue is the variability in lifespan between different model organisms. Take liver disease as an example, around one in four people will suffer from liver disease in their lifetime, but currently around one in six people will live to be a centenarian, which is incomparable to transient animal models of . As the average human life expectancy increases, so does the incidence of various chronic diseases, adding biological complexity that animal models fail to account for. Ocher Biomedical hopes to take advantage of the general trend of the data revolution and find solutions for the drug development process.
Using the human body as a model and using computer simulation technology to screen data
Through major advances in biotechnology such as the Human Genome Project, the scientific community hopes that more data will fuel an explosion of new treatments. However, more data is only one factor in drug development. In fact, even with the large amount of genomic data generated, there have not been a large number of new treatments. While trying to answer this question, Dr. Wills concludes that not all types of data are created equal. With a renewal of thinking, Dr. Wills and the ocr team use more advanced algorithms to generate and search for translatable data, raising the use of biological information to a new level.
Ocher Biomedical’s laboratory in Taiwan uses livers donated from local morbidly obese individuals, obtains dozens of tissue sections from patient biopsies, treats these sections in vitro, and studies the effects of different treatments on different patient samples. The team analyzed dozens of cell populations from the samples, and combined with single-cell sequencing technology, observed the behavior of genes in a variety of cells, including bile, neurons, endothelial cells, circulating endothelial cells (endothelial cells that n circulating), resident of the liver. macrophages (resident macrophage) and lipid-associated macrophage (lipid-associated macrophage). The team is now using the data from the study to actively search for new gene targets for treating chronic liver disease.
Dr said. Wills that single cell sequencing is an excellent and revolutionary technology, but if the data obtained from it is to be used to develop new treatments, proper preparation must be done in advance. Through tailored data collection and analysis methods, the Ocher team’s understanding of this great endocrine organ is constantly expanding.
With the dramatic technological advances of the last few decades, complex and sophisticated computer models have formed a separate research category called “computer simulations” (in silico), the in vivo control (live) or in vitro (in vitro) Research. Ocher Biomedical uses its expertise in artificial intelligence and big data to develop in silico screening techniques to help identify new targets and inform drug development.
Ocher Biomedical spatially followed approximately 1,000 human livers in its laboratory in Oxford, UK, and genetically mapped the resulting data to histological and clinical characteristics. Dr. Cred Wills that the process, although quite expensive and complex, is particularly valuable for this early stage of computational biology.
First, the Oxford laboratory team made a set of sections stained using the histological stains hematoxylin and eosin, commonly used in medical diagnosis, and divided them into regions. The scientists then put the slices through a trained neural network to create a low-dimensional projection with similar features. Using these advanced techniques, the team determined a series of characteristics such as tissue disease phenotype and spatial transcriptome of the experimental liver. What’s more, the team used in silico screening techniques to target approximately 150 blood and clinical features, enabling them to identify multiple potential new therapeutic targets for liver disease-specific modifications.
Ocher Biomedical continues to open prospects in the field of biotechnology
Dr said. Wills, in addition to existing research programs, the company also plans to initiate the world’s first single-cell CRISPR sequencing model in the whole human liver. This technique has been used by scientists on other human samples in the past, but as far as he knows, no one has used it on a complete human organ until now.
With an increasing volume of CRISPR data worldwide, he believes that the company’s models will one day be able to make predictions based on the resulting data, providing unique solutions at an unprecedented speed.
Seeking an innovative point to allow new businesses to keep pace with large pharmaceutical companies
Dr. Lin Yanzhu, CEO of Insilico Medicine Taiwan, shared the main business of Insilico Medicine In general, traditional drug development takes more than ten years and costs about US$1.8 billion on average. To reduce the time and cost required for the drug discovery and development process, Insilico plans to use artificial intelligence to revolutionize the status quo.
Artificial intelligence is not a new technology, but recent developments in related fields have highlighted the technology’s potential for drug discovery. Dr Lin also pointed out that in 2021, the top 20 AI companies in the world have multiple assets that can compete with the top 20 pharmaceutical companies, which is enough to prove that AI can help small companies move their product lines rapidly progress to the clinic stage. .
A new platform redefines spatial proteomics discovery
Currently, it is difficult for scientists to identify proteomes based on morphology, and there are no suitable tools to facilitate the discovery of high-precision spatial proteomics. Although imaging techniques have been instrumental in spatially resolved protein identification, it is impractical to repeatedly stain with multiple antibodies to study the distribution of mutations once they occur.
In view of this, Professor Liao Zhongqi, CEO of New Analysis Biotechnology, proposed a new alternative solution. Its MicroScoop facilitates high-content, image-guided optical labeling by integrating microscopy, deep learning, two-photon illumination, and mechatronics, enabling hypothesis-free proteomic discovery in subcellular spaces. Furthermore, this new technique can precisely label spatially specific proteins from hundreds of thousands of individual cells with sufficient sensitivity for mass spectrometry analysis, redefining spatial proteomics discovery as we know it today.
Using NGS and AI to Guide Immuno-Oncology Therapy Design
In the final presentation, Dr. Chen Yingjia, R&D Manager of Acer’s Value Innovation Center, shared how next-generation sequencing (NGS) and artificial intelligence can guide the design of immuno-oncology therapies, including personalized cancer vaccines. Dr. Chen pointed out that cancer mutation analysis can be very useful in clinical research with the development of NGS technology. On the other hand, a detailed analysis of cancer characteristics can better dissect the status of tumors and provide direction for treatment options. Cooperating with artificial intelligence and big data, more new ways of drug discovery will emerge in the future.
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