FDA Moves to Modernize Drug Review Process

Under a new “knowledge management” approach for the Center for Drug Evaluation and Research (CDER), sponsors will submit applications that present data in a structured format so that it can be transmitted to teams of experts from multiple disciplines able to assess applications for new drugs and biologics in a timely and efficient manner. The aim is to shift sponsors away from long, narrative documents filed in PDF format that are repetitive and obscure important issues. Instead, CDER assessment teams composed of medical reviewers, pharmacologists, statisticians, pharmacists and other specialists as needed will examine the data to answer specific questions relevant to the product under review. CDER director Janet Woodcock is finalizing this process for assessing and approving new drugs in order to be able to handle a surge in submissions that reflects important advances in biopharmaceutical science, as well as the digital revolution that has expanded exponentially the data and information supporting biomedical research. 

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PracticeMatch

PracticeMatch connects physicians and advanced practitioners with potential employers through a unique set of sourcing tools, allowing both to find their perfect match. Company Overview PracticeMatch is the premier source for physician data and recruitment services for in-house physician recruiters. We are backed by the strength of our graduating and practicing physician databases-- the two most highly-regarded databases in the industry.

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MedTech

Data Analytics: A Groundbreaking Technology in Biotech

Article | September 22, 2022

Biotechnology is a vast discipline of biology that employs diverse biological systems to create solutions that can significantly alter the ways in which they operate across various domains. That said, biotechnology is not a new notion. It has existed for millennia, with ancient civilizations using its earliest incarnations to cultivate crops and create alcoholic beverages. Today, the biotechnology industry has developed by leaps and bounds and has amassed a vast quantity of scientific data through study and research. Given the importance of data in the biotechnology business, it is not difficult to understand why biotech companies utilize data analytics. Modern data analytics tools have made it possible for researchers in the biotech industry to build predictive analytics models and gain knowledge about the most efficient approaches to accomplish their desired goals and objectives. Data analytics is increasingly being adopted by biotech businesses to better understand their industry and foresee any problems down the road. How is Data Analytics Revolutionizing Fields in Biotechnology? Today's business and scientific fields greatly benefit from data. Without the analysis of vast information libraries that provide new insights and enable new innovations, no industry can really advance. Being highly reliant on big data analytics, biotech is not an exception in this regard. With the tools and methods that help scientists systematize their findings and speed up their research for better and safer results, data analytics is making deeper inroads into the biotechnology industry. It is emerging as a crucial link between knowledge and information and is extensively being used for purposes other than just examining the information that is already available. The following are a few of the cutting-edge biotechnology applications of data analytics Genomics and Disease Treatment Pharmaceutical Drug Discovery Drug Recycling and Safety Agriculture and Agri-products Environmental Damage Mitigation Data Analytics Possibilities in Biotechnology With data analytics becoming an integral part of how biotech businesses operate, biotechnologists and related stakeholders need to understand its emergence and crucial role. Data analytics has opened new frontiers in the realm of biotechnology. Thanks to developments in data analytics, research and development activities that once took years may now be accomplished in a matter of months. Also, now scientists have access to biological, social, and environmental insights that can be exploited to create more effective and sustainable products. By understanding the importance of data-related tools and techniques applications, biotech companies are aiming to invest in the popularizing technology to stay updated in the fast-paced biotechnology industry.

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MedTech

Biotech in 2022

Article | July 11, 2022

The robust global channel of more than, 800 gene and cell curatives presently in trials will produce clinical readouts in 2022, revealing what lies ahead for advanced curatives. The impact will be felt in 2022, no matter how you slice it. Eventually, how well industry and non-supervisory bodies unite to produce new frameworks for advanced therapies will shape the year 2022 and further. Pacific Northwest talent will continue to contribute to the advancement of gene and cell curatives in both the short and long term, thanks to its deep pool of ground-breaking scientific developers, entrepreneurial directorial leadership, largely skilled translational scientists, and endured bio manufacturing technicians. We may see continued on-life science fund withdrawal from biotech in 2021, but this can be anticipated as a strong comeback in 2022 by biotech industry, backed by deep-pocketed life science investors who are committed to this sector. A similar investment, combined with pharma's cash-heavy coffers, can result in increased junction and acquisition activity, which will be a challenge for some but an occasion for others. Over the last five years, investment interest in Seattle and the Pacific Northwest has grown exponentially, from Vancouver, British Columbia, to Oregon. The region's explosive portfolio of new biotech companies, innovated out of academic centres, demonstrates the region's growing recognition of scientific invention. This created a belief that continued, especially because Seattle's start-ups and biotech enterprises are delivering on their pledge of clinical and patient impact. Talent and staffing will continue to be difficult to find. It's a CEO's market, but many of these funds' return, and are not rising in proportion to the exorbitant prices they're paying to enter deals. This schism has become particularly pronounced in 2021. Hence, everyone in biotech is concerned about reclamation and retention.

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MedTech

Wisconsin biotech companies could play key roles in long-term economic recovery from COVID-19 pandemic

Article | July 12, 2022

Whether it’s called a modern “Manhattan Project” or a medical moon shot, the concept of long-term economic recovery rests on how confident people are they won’t risk serious illness by venturing forth in public again. Wisconsin stands to be a significant part of such an undertaking, whatever it’s called. The shorter-term debate is well under way over the gradual lifting of COVID-19 emergency rules, such as the now-extended “safer-at-home” order in Wisconsin. At least a dozen states, including regional coalitions on the East and West coasts, are exploring next steps as they seek to balance responses to the virus with calls for reopening the economy, at least, in part. Wisconsin’s ability to shape longer-term responses will come from private and public resources, which range from companies engaged in production of diagnostics.

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MedTech

Top 3 Biotech Clinical Data Management Trends to Watch in 2022

Article | September 22, 2022

Introduction The administration of medical records and data has advanced significantly during the past few decades. Clinical data management, which was once only a small subset of biotech research organizations, has now developed into a mission-critical, specialized unit. In the late 1990s, electronic data capture (EDC) began to alter the traditional function of clinical data management. After that, the data configuration and management of data queries for the EDC system fell under the purview of clinical data management services. Today, clinical data management is not only responsible for managing the clinical data configuration and data queries but also developing and implementing data administration plans, ensuring data accuracy and completeness, and maintaining optimum data security. In recent years, as digital technologies have gained acceptance around the globe, data has become a vital aspect in decision-making across numerous industries, and the life sciences and biotechnology sectors are no exception. Using data has provided granular insights to biotech organizations, assisting them in creating breakthroughs in drug development and medical research and signifying the importance of clinical trial management systems in these medical verticals. The Biggest Biotech Clinical Data Management Trends to Know About Today The future of clinical data management is contingent upon the implementation of systems and regulations. It is imperative for all organizations participating in a medical or life science trial to have transparent rules in place for sharing and retaining patient data. Also, there is a need to have a standardized format for maintaining these records and documents related to trials. This assists biotech organizations in reducing the chances of ambiguity regarding who owns what kind of data or paperwork at any given time. Over the past couple of years, the focus of the life science and biotechnology industries has shifted towards developing more effective medications and therapies, implementing personalized treatment, and finding cures for diseases such as cancer and AIDS. In response to this, a substantial rise in the number of clinical trials is being witnessed globally. As the number of clinical trials continues to accelerate, the spending on these trials rises as well. In response to this, the worldwide cost of conducting clinical trials is anticipated to reach US$ 49.80 billion in 2022. With the transition of the world from traditional to digital, medical professionals and biotech businesses are increasingly shifting towards adopting high-tech and reliable clinical trial management systems for various applications, starting from diagnosis and clinical trials to patient data documentation. But, what are the future trends in biotechnology clinical data management? Let’s discuss. Cloud-Based Clinical Metadata Repositories Automation is emerging as a new frontier in the biotech clinical data management domain, along with other innovative technologies such as artificial intelligence and machine learning. Because of this, life science establishments are witnessing a huge shift from paper-based documentation toward data-based documentation, which is creating mountains of research, compliance, and clinical data. The growing demand for new and more effective medications and drugs is augmenting the need to expedite clinical trials. This is resulting in an increased number of initiatives aimed at optimizing clinical trial processes to prepare and launch successful trials. However, pharmaceutical and biotechnology laboratories are encountering several challenges in collecting, managing, and analyzing metadata due to its complexities. So, what is the best solution to this problem? The answer to this is cloud-based clinical metadata repositories. Clinical research facilities are leveraging advanced, all-in-one, cloud-based clinical metadata repositories to assist them in centralizing and managing metadata; increasing metadata quality, consistency, and accuracy; and speeding up clinical trial management, documentation, and compliance processes. Shift Towards Digital Solutions Electronic Case Report Form Adequate research and accurate data are crucial for a clinical trial to succeed. Whether developing new drugs, medication, or therapies; conducting life science research; or studying the latest clinical trial systems, it is best to use electronic solutions as it reduces the room for mistakes during the transition of clinical data from paper-based format. Realizing this, biotech organizations are shifting towards using electronic case report forms to speed up record retrieval, improve record security, and cut down on operational costs associated with running clinical trials. The electronic case report form assists in lowering the failure rate of the clinical trial, enhancing efficiency, and optimizing security along with improving clinical trial documentation and productivity, further driving its adoption in the medical space. Electronic Clinical Outcome Assessment Electronic clinical outcome assessment is surfacing as one of the fast-growing future trends in biotechnology. It allows clinical trial facilities to automate data entry and improve the reliability of the collected information. The technology enables clinical trial institutions to automatically record patient-provided information about side effects, symptoms, drug timing, and other aspects during the clinical trial for increased precision. It also helps these institutions analyze the results of medication or therapy in clinical trials and lets clinical researchers use medical technologies like biosensor-enabled devices, self-service applications, and medical wearables for evaluation. Hence, biotech clinical facilities are increasingly deploying advanced electronic clinical outcome assessment systems to ensure adherence to protocols and regulations. Clinical Trial Customization The success of a new drug is determined by numerous factors other than its effectiveness, safety, and creativity of its developers, such as a successful clinical trial. Each clinical trial involves a number of decision-making points, and one wrong choice in any of these aspects can jeopardize the success of the entire endeavor. A crucial component of making well-informed decisions is data management, which is a part of clinical study as a whole. Clinical trial customization is emerging as one of the most prominent biotech clinical trial management trends. Every clinical trial is unique and needs a tailored approach to be successful. With the emergence of the trend of personalized treatment around the globe, biotech and pharmaceutical organizations are adopting innovative customized clinical trial management solutions to accelerate the pace of clinical trials and approvals. This is giving clinical researchers innovative ways to come up with new medicines for patients and streamline the clinical data as per the requirements for faster approvals. What Are the Key Clinical Data Management Challenges Faced by Biotech Companies? Groundbreaking medical interventions are of no use without reliable, accurate, and extensive clinical trial data. Without the data, biotech and pharmaceutical companies will not be able to provide the assurance of safety and efficacy required to bring the medication to market. Regulatory bodies such as the Food and Drug Administration (FDA), the Medicines and Healthcare Products Regulatory Agency (MHRA), and others are putting stricter rules in place to ensure the quality of clinical data. In addition, the fast-changing clinical development environment is creating more obstacles for biotech and medical spaces to ensure the accuracy, standard, and completeness of the clinical trial data. Hence, clinical teams are spending valuable time cleaning up data instead of analyzing it. Time spent trying to figure out issues with clinical trial data is detrimental and expensive but also mission-critical. This is because a small issue in the data can lead to numerous consequences, from small delays to calamitous setbacks, making it necessary to rerun clinical trials. This problem will only get more challenging to address as the volume of data and the types of data sources continue to grow. Here are some of the major clinical data management challenges that biotech firms encounter Standardization of Clinical Metadata Stringent Regulatory Compliance Increased Clinical Trial Complexity Mid-Study Changes Why Are Clinical Data Management Systems Garnering Popularity in the Biotech Industry? With the changing regulatory and clinical landscape, biotech and pharmaceutical companies are facing several obstacles in the management of clinical data and clinical trials. In addition, regulatory agencies are moving toward integrated electronic systems, which is making it more and more important for clinical laboratories to change the format of their submissions. Because of this, several biotech clinical labs are focusing on adopting innovative laboratory solutions, such as biotech clinical data management systems, to meet the need for standardized data inputs and replace all manual ways of working with electronic systems. A clinical data management system establishes the framework for error-free data collection and high-quality data submission, resulting in speedier drug discovery and shorter time-to-market. These solutions are gaining huge traction among biotech and pharmaceutical companies, owing to their ability to effectively manage clinical data, accelerate clinical trials, and ensure compliance. Let’s see some of the features of biotech clinical data management software that are most sought after by life-science companies Controlled, standardized data repository. Centralized data analysis and administration. Reduced operational expenditures for clinical data processes. Enhanced process effectiveness. Superior submission quality Compliance with predefined standards. Clinical Data Management Systems: The Future The role of clinical data management systems is evolving at a rapid pace as the life science and medical industries continue to incorporate digital solutions for diverse operations. These systems are being used in a variety of biotech clinical settings, ranging from clinical data compliance to data science and analytics, to help them analyze large and growing volumes of clinical data. Hence, a number of high-tech medical companies are aiming at integrating innovative technologies, such as artificial intelligence and machine learning, into clinical data management software to automate clinical data management tasks, improve clinical data submission, and enhance data quality. These new biotech clinical management technologies are anticipated to help life science laboratories gain a better understanding of diseases and speed up clinical trials in the coming years. FAQ What is a clinical data management system? A clinical data management system (CDMS) is a tool used in clinical research to track, record, and manage clinical trial data across medical establishments such as biotech laboratories. What are the key functions of the biotech clinical data management system? Some of the key functions of biotech clinical data management system are Documentation of Protocols and Regulations Patient Recruitment Real-time Clinical Study Analytics Reporting Investigator Relationship Management Electronic Visit Report Why is a clinical data management system needed for clinical trials today? A clinical data management system helps shorten the time from drug development to marketing by assisting in the collection of high-quality, statistically sound, and accurate data from clinical trials.

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PracticeMatch

PracticeMatch connects physicians and advanced practitioners with potential employers through a unique set of sourcing tools, allowing both to find their perfect match. Company Overview PracticeMatch is the premier source for physician data and recruitment services for in-house physician recruiters. We are backed by the strength of our graduating and practicing physician databases-- the two most highly-regarded databases in the industry.

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NiKang Therapeutics Completes $200 Million Series C Financing to Advance Highly Differentiated Small Molecules Addressing Difficult-to-Drug Targets

NiKang Therapeutics | May 31, 2021

NiKang Therapeutics Inc., a clinical-stage biotech company focused on developing innovative small molecule oncology medicines to assist patients with unmet medical needs; today announced the completion of an oversubscribed $200 million Series C financing led by Cormorant Asset Management, HBM Healthcare Investments, and Octagon Capital Advisors with participation from a premier syndicate of funds, including new investors EcoR1 Capital, Perceptive Advisors, Wellington Management, Ally Bridge Group, Pavilion Capital, funds and accounts managed by BlackRock, RA Capital Management, Surveyor Capital (a Citadel company), Samsara BioCapital, PFM Health Sciences, Invus, Janus Henderson Investors and Logos Capital. All existing investors, including CBC Group, RTW Investments, LP, Lilly Asia Ventures, Matrix Partners China, and Casdin Capital, participated in the financing. About the funding, Bing Yao, Ph.D., former CEO and chairman of Viela Bio, and Ting Jia, Ph.D., founder and chief investment officer of Octagon Capital Advisors, will join NiKang’s Board of Directors. “We are thrilled to have such an outstanding group of investors as our shareholders,” said Zhenhai Gao, Ph.D., co-founder, president, and chief executive officer of NiKang. “Their support of our vision allows us to build the world’s leading precision oncology company. We are now well-positioned to rapidly advance our pipeline into the clinic, including our differentiated HIF-2 alpha inhibitor, and to bring our company to the next level of growth.” “This financing is a testament to the quality of our science and team,” Kelsey Chen, Ph.D., MBA, chief financial officer, added. “Since joining NiKang, I have witnessed the passion and dedication of a group of talented scientists who are devoting their lives to advancing treatments for patients. We are grateful to be recognized by such a high-caliber group of investors.” “NiKang has made remarkable progress over the last eight months since our initial investment,” said Ting Jia, Ph.D., a chief investment officer of Octagon. “We are impressed by the team’s accomplishment. We believe NiKang’s unique approach to attacking difficult-to-drug targets offers promising opportunities to develop breakthrough treatments for cancer patients. We are excited to co-lead the series C financing and partner with the NiKang team to accelerate its growth.” “We are proud of what NiKang has achieved since its inception,” said Sean Cao, executive chairman of NiKang and managing director of CBC Group, which incubated the company. “The strength of this group of investors validates NiKang’s achievements and demonstrates their confidence in NiKang’s potential to grow into a leading innovative drug company.” Proceeds will be used to advance the company’s lead drug candidates into the clinic, expand the pipeline, and fund internal drug discovery programs. About NiKang Therapeutics NiKang Therapeutics is a clinical-stage biotech company focused on discovering and developing innovative small molecule oncology medicines to assist patients with unmet medical needs. Our target selection is driven by deep insights into disease biology and molecular pathways. Our discovery approach is informed by target structure biology and capitalizes on structure-based drug design. The successful implementation of our strategy enables us to rapidly and efficiently discover and advance proprietary drug candidates with the most desirable pharmacological features into clinical studies. We strive to bring transformative medicines to patients in need.

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Medical

TeselaGen Biotechnology Announced the Launch of a New Protein Optimization Toolkit for Automated Biotherapeutic Drug Design and Development

TeselaGen Biotechnology | May 21, 2021

TeselaGen Biotechnology today announced the launch of a new protein optimization toolkit for biotherapeutic drug design and development, introducing significant enhancements to the company’s flagship TeselaGen® OS to form designing and developing pharmaceuticals and biotherapeutics faster and fewer expensive. The new capabilities, easily accessible via the cloud-based platform, simplify the planning of highly complex combinatorial protein libraries and support AI models for optimizing new peptides and proteins. New application programming interfaces (APIs) and integration tools have also been extended to further enhance users’ access to the new capabilities. TeselaGen integrates the facility of AI with one end-to-end platform for design, construction, data gathering, and analysis of bioproduct performance, from pharmaceuticals to food and fabrics, significantly accelerating time to plug and reducing costs. The platform’s DESIGN, BUILD, TEST, and find out modules enable researchers to effectively collaborate across an organization's development pipeline to style and build experiments, standardize and share data, and learn and preserve project results by embedding them during a machine learning model. TeselaGen’s DESIGN is an intuitive, user-interface-driven module that permits scientists to style highly complex combinatorial libraries. With this new release, the planning now supports aminoalkanoic acid parts which will be efficiently mapped to DNA. TeselaGen can then automatically generate biology protocols for efficiently synthesizing and assembling the corresponding DNA libraries. TeselaGen’s DISCOVER now supports AI models which will recommend new peptides and proteins supported by the training of supervised and unsupervised learning models. The platform also supports the modeling of unnatural amino acids and multicriteria optimization of proteins. R&D groups can utilize the TeselaGen OS to hurry the invention process. Datasets are uploaded and arranged within the platform and immediately useful for model building within TeselaGen’s DISCOVER module. TeselaGen has demonstrated that it can increase the planning and build speed of biological products and reduce the prices related to research & development by an order of magnitude. Current partnering companies are using the new capabilities for designing antibodies and optimizing their binding affinity, titer, specific productivity, immunogenicity, or other phenotypic variables of interest. Researchers also are looking to TeselaGen for rapidly engineering new vaccines - using methods like virus-like particles (VLPs), DNA, and RNA vaccines - opening the door to attacking rapidly mutating RNA and retroviruses like influenza, HCV, HIV, or coronaviruses. About TeselaGen Biotechnology TeselaGen Biotechnology has developed the primary artificial intelligence-enabled OS for biotechnology, enabling the event and commercialization of high-performance bioproducts – from pharmaceuticals to food to fabrics – faster and easier than ever. TeselaGen® connects biologists, lab technicians, and bioinformaticians so that they will collaboratively design and build experiments, organize and standardize data then test and continually learn from the info. TeselaGen has been deployed by Fortune 50 companies and emerging innovators in biopharmaceuticals, agriculture, and specialty chemicals. the corporate is privately held and based in San Francisco, California.

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AI

Iktos Partners with Kadmon to Use AI for New Drug Design

Iktos, Kadmon | May 19, 2021

Iktos, a company specializing in Artificial Intelligence for new drug design, announced today that it has signed a Research Collaboration Agreement with Kadmon, a clinical-stage biopharmaceutical company based in New York, USA, under which Iktos' generative modeling artificial intelligence (AI) technology will be used to allow the rapid and cost-effective design of novel drug candidates. Iktos will use its de novo structure-based generative modeling technologies to find novel compounds that meet a pre-defined target product profile as part of the deal, to speed up Kadmon's early-stage discovery efforts. Kadmon discovers, develops, and delivers small molecules and biologics for the treatment of human diseases. Intending to identify and develop new product candidates for significant unmet medical needs, Kadmon is expanding and incorporating novel drug discovery platforms. The AI technology developed by Iktos, which is focused on deep generative models, aids in the speed and efficiency of the drug discovery process. Iktos' technology creates virtual novel molecules that have all of the properties of a successful drug molecule automatically. This approach, which has been validated by Iktos' other collaborations, is an innovative approach to one of the most difficult problems in drug design: finding molecules that meet several important drug criteria at the same time, such as potency, selectivity, safety, and project-specific properties. Iktos' technology enables the creation of new hits with optimal protein-ligand interactions in early-stage discovery projects, as predicted by molecular modeling technology. This technique allows for a one-of-a-kind discovery of chemical space, as well as the development of innovative molecule designs with greater Freedom to Operate. Furthermore, allowing multi-parametric in silico optimization from the start of a project greatly reduces the hit finding and hit-to-lead optimization phases. About Iktos Iktos, a French start-up founded in October 2016, specializes in the development of artificial intelligence technologies for chemical research, especially medicinal chemistry, and new drug design. Iktos is working on a proprietary and innovative approach focused on deep learning generative models that allow users to build molecules in silico that follow all of the performance criteria of a small molecule discovery project using existing evidence. Iktos technology allows for significant efficiency gains in upstream pharmaceutical R&D. Iktos' software is utilized as both professional services and a SaaS software platform, Makya. Spaya, a synthesis planning software built on Iktos' proprietary AI technology for retrosynthesis, is also in the works.

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NiKang Therapeutics Completes $200 Million Series C Financing to Advance Highly Differentiated Small Molecules Addressing Difficult-to-Drug Targets

NiKang Therapeutics | May 31, 2021

NiKang Therapeutics Inc., a clinical-stage biotech company focused on developing innovative small molecule oncology medicines to assist patients with unmet medical needs; today announced the completion of an oversubscribed $200 million Series C financing led by Cormorant Asset Management, HBM Healthcare Investments, and Octagon Capital Advisors with participation from a premier syndicate of funds, including new investors EcoR1 Capital, Perceptive Advisors, Wellington Management, Ally Bridge Group, Pavilion Capital, funds and accounts managed by BlackRock, RA Capital Management, Surveyor Capital (a Citadel company), Samsara BioCapital, PFM Health Sciences, Invus, Janus Henderson Investors and Logos Capital. All existing investors, including CBC Group, RTW Investments, LP, Lilly Asia Ventures, Matrix Partners China, and Casdin Capital, participated in the financing. About the funding, Bing Yao, Ph.D., former CEO and chairman of Viela Bio, and Ting Jia, Ph.D., founder and chief investment officer of Octagon Capital Advisors, will join NiKang’s Board of Directors. “We are thrilled to have such an outstanding group of investors as our shareholders,” said Zhenhai Gao, Ph.D., co-founder, president, and chief executive officer of NiKang. “Their support of our vision allows us to build the world’s leading precision oncology company. We are now well-positioned to rapidly advance our pipeline into the clinic, including our differentiated HIF-2 alpha inhibitor, and to bring our company to the next level of growth.” “This financing is a testament to the quality of our science and team,” Kelsey Chen, Ph.D., MBA, chief financial officer, added. “Since joining NiKang, I have witnessed the passion and dedication of a group of talented scientists who are devoting their lives to advancing treatments for patients. We are grateful to be recognized by such a high-caliber group of investors.” “NiKang has made remarkable progress over the last eight months since our initial investment,” said Ting Jia, Ph.D., a chief investment officer of Octagon. “We are impressed by the team’s accomplishment. We believe NiKang’s unique approach to attacking difficult-to-drug targets offers promising opportunities to develop breakthrough treatments for cancer patients. We are excited to co-lead the series C financing and partner with the NiKang team to accelerate its growth.” “We are proud of what NiKang has achieved since its inception,” said Sean Cao, executive chairman of NiKang and managing director of CBC Group, which incubated the company. “The strength of this group of investors validates NiKang’s achievements and demonstrates their confidence in NiKang’s potential to grow into a leading innovative drug company.” Proceeds will be used to advance the company’s lead drug candidates into the clinic, expand the pipeline, and fund internal drug discovery programs. About NiKang Therapeutics NiKang Therapeutics is a clinical-stage biotech company focused on discovering and developing innovative small molecule oncology medicines to assist patients with unmet medical needs. Our target selection is driven by deep insights into disease biology and molecular pathways. Our discovery approach is informed by target structure biology and capitalizes on structure-based drug design. The successful implementation of our strategy enables us to rapidly and efficiently discover and advance proprietary drug candidates with the most desirable pharmacological features into clinical studies. We strive to bring transformative medicines to patients in need.

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Medical

TeselaGen Biotechnology Announced the Launch of a New Protein Optimization Toolkit for Automated Biotherapeutic Drug Design and Development

TeselaGen Biotechnology | May 21, 2021

TeselaGen Biotechnology today announced the launch of a new protein optimization toolkit for biotherapeutic drug design and development, introducing significant enhancements to the company’s flagship TeselaGen® OS to form designing and developing pharmaceuticals and biotherapeutics faster and fewer expensive. The new capabilities, easily accessible via the cloud-based platform, simplify the planning of highly complex combinatorial protein libraries and support AI models for optimizing new peptides and proteins. New application programming interfaces (APIs) and integration tools have also been extended to further enhance users’ access to the new capabilities. TeselaGen integrates the facility of AI with one end-to-end platform for design, construction, data gathering, and analysis of bioproduct performance, from pharmaceuticals to food and fabrics, significantly accelerating time to plug and reducing costs. The platform’s DESIGN, BUILD, TEST, and find out modules enable researchers to effectively collaborate across an organization's development pipeline to style and build experiments, standardize and share data, and learn and preserve project results by embedding them during a machine learning model. TeselaGen’s DESIGN is an intuitive, user-interface-driven module that permits scientists to style highly complex combinatorial libraries. With this new release, the planning now supports aminoalkanoic acid parts which will be efficiently mapped to DNA. TeselaGen can then automatically generate biology protocols for efficiently synthesizing and assembling the corresponding DNA libraries. TeselaGen’s DISCOVER now supports AI models which will recommend new peptides and proteins supported by the training of supervised and unsupervised learning models. The platform also supports the modeling of unnatural amino acids and multicriteria optimization of proteins. R&D groups can utilize the TeselaGen OS to hurry the invention process. Datasets are uploaded and arranged within the platform and immediately useful for model building within TeselaGen’s DISCOVER module. TeselaGen has demonstrated that it can increase the planning and build speed of biological products and reduce the prices related to research & development by an order of magnitude. Current partnering companies are using the new capabilities for designing antibodies and optimizing their binding affinity, titer, specific productivity, immunogenicity, or other phenotypic variables of interest. Researchers also are looking to TeselaGen for rapidly engineering new vaccines - using methods like virus-like particles (VLPs), DNA, and RNA vaccines - opening the door to attacking rapidly mutating RNA and retroviruses like influenza, HCV, HIV, or coronaviruses. About TeselaGen Biotechnology TeselaGen Biotechnology has developed the primary artificial intelligence-enabled OS for biotechnology, enabling the event and commercialization of high-performance bioproducts – from pharmaceuticals to food to fabrics – faster and easier than ever. TeselaGen® connects biologists, lab technicians, and bioinformaticians so that they will collaboratively design and build experiments, organize and standardize data then test and continually learn from the info. TeselaGen has been deployed by Fortune 50 companies and emerging innovators in biopharmaceuticals, agriculture, and specialty chemicals. the corporate is privately held and based in San Francisco, California.

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AI

Iktos Partners with Kadmon to Use AI for New Drug Design

Iktos, Kadmon | May 19, 2021

Iktos, a company specializing in Artificial Intelligence for new drug design, announced today that it has signed a Research Collaboration Agreement with Kadmon, a clinical-stage biopharmaceutical company based in New York, USA, under which Iktos' generative modeling artificial intelligence (AI) technology will be used to allow the rapid and cost-effective design of novel drug candidates. Iktos will use its de novo structure-based generative modeling technologies to find novel compounds that meet a pre-defined target product profile as part of the deal, to speed up Kadmon's early-stage discovery efforts. Kadmon discovers, develops, and delivers small molecules and biologics for the treatment of human diseases. Intending to identify and develop new product candidates for significant unmet medical needs, Kadmon is expanding and incorporating novel drug discovery platforms. The AI technology developed by Iktos, which is focused on deep generative models, aids in the speed and efficiency of the drug discovery process. Iktos' technology creates virtual novel molecules that have all of the properties of a successful drug molecule automatically. This approach, which has been validated by Iktos' other collaborations, is an innovative approach to one of the most difficult problems in drug design: finding molecules that meet several important drug criteria at the same time, such as potency, selectivity, safety, and project-specific properties. Iktos' technology enables the creation of new hits with optimal protein-ligand interactions in early-stage discovery projects, as predicted by molecular modeling technology. This technique allows for a one-of-a-kind discovery of chemical space, as well as the development of innovative molecule designs with greater Freedom to Operate. Furthermore, allowing multi-parametric in silico optimization from the start of a project greatly reduces the hit finding and hit-to-lead optimization phases. About Iktos Iktos, a French start-up founded in October 2016, specializes in the development of artificial intelligence technologies for chemical research, especially medicinal chemistry, and new drug design. Iktos is working on a proprietary and innovative approach focused on deep learning generative models that allow users to build molecules in silico that follow all of the performance criteria of a small molecule discovery project using existing evidence. Iktos technology allows for significant efficiency gains in upstream pharmaceutical R&D. Iktos' software is utilized as both professional services and a SaaS software platform, Makya. Spaya, a synthesis planning software built on Iktos' proprietary AI technology for retrosynthesis, is also in the works.

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