Cytion SA (TransSense Sarl)

Description

Cytion SA, also known as TransSense Sarl, is a life science company dedicated to equipping researchers with next-generation technology to advance scientific discovery and improve human life worldwide. With a focus on 3D biology, Cytion SA pioneers the future of drug discovery by leveraging proprietary bioprocess technology to produce reliable and predictive organoids at scale. Their Organoid Innovation Center combines cutting-edge technologies with novel research methods to address key challenges in scaling complex 3D biological models. By offering automated 3D bioprinting solutions, cell engineering services, and lab automation customization, Cytion SA empowers scientists to advance discovery and industrialize biology.

Official source

https://www.moleculardevices.com

About this result

This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Categories (4)

Related concepts (5)

Related courses (15)

Related lectures (21)

Related people (9)

Related publications (28)

Related startups (1)

Related units (14)

Drug discovery

In the fields of medicine, biotechnology and pharmacology, drug discovery is the process by which new candidate medications are discovered. Historically, drugs were discovered by identifying the active ingredient from traditional remedies or by serendipitous discovery, as with penicillin. More recently, chemical libraries of synthetic small molecules, natural products or extracts were screened in intact cells or whole organisms to identify substances that had a desirable therapeutic effect in a process known as classical pharmacology.

Drug design

Drug design, often referred to as rational drug design or simply rational design, is the inventive process of finding new medications based on the knowledge of a biological target. The drug is most commonly an organic small molecule that activates or inhibits the function of a biomolecule such as a protein, which in turn results in a therapeutic benefit to the patient. In the most basic sense, drug design involves the design of molecules that are complementary in shape and charge to the biomolecular target with which they interact and therefore will bind to it.

Fragment-based lead discovery

Fragment-based lead discovery (FBLD) also known as fragment-based drug discovery (FBDD) is a method used for finding lead compounds as part of the drug discovery process. Fragments are small organic molecules which are small in size and low in molecular weight. It is based on identifying small chemical fragments, which may bind only weakly to the biological target, and then growing them or combining them to produce a lead with a higher affinity. FBLD can be compared with high-throughput screening (HTS).

Drug development

Drug development is the process of bringing a new pharmaceutical drug to the market once a lead compound has been identified through the process of drug discovery. It includes preclinical research on microorganisms and animals, filing for regulatory status, such as via the United States Food and Drug Administration for an investigational new drug to initiate clinical trials on humans, and may include the step of obtaining regulatory approval with a new drug application to market the drug.

Computational biology

Computational biology refers to the use of data analysis, mathematical modeling and computational simulations to understand biological systems and relationships. An intersection of computer science, biology, and big data, the field also has foundations in applied mathematics, chemistry, and genetics. It differs from biological computing, a subfield of computer engineering which uses bioengineering to build computers. Bioinformatics, the analysis of informatics processes in biological systems, began in the early 1970s.

Drug discovery

Pharmacology

Pharmacology is a branch of medicine, biology, and pharmaceutical sciences concerned with drug or medication action, where a drug may be defined as any artificial, natural, or endogenous (from within the body) molecule which exerts a biochemical or physiological effect on the cell, tissue, organ, or organism (sometimes the word pharmacon is used as a term to encompass these endogenous and exogenous bioactive species). It is the science of drugs including their origin, composition, pharmacokinetics, therapeutic use, and toxicology.

Health sciences

The following outline is provided as an overview of and topical guide to health sciences: Health sciences are those sciences which focus on health, or health care, as core parts of their subject matter. Health sciences relate to multiple academic disciplines, including STEM disciplines and emerging patient safety disciplines (such as social care research). Medicine is an applied science or practice of the diagnosis, treatment, and prevention of disease.

Applied sciences

The following outline is provided as an overview of and topical guide to applied science: Applied science – the branch of science that applies existing scientific knowledge to develop more practical applications, including inventions and other technological advancements. Science itself is the systematic enterprise that builds and organizes knowledge in the form of testable explanations and predictions about the universe. Applied cryptography – applications of cryptography.

Cytion SA (TransSense Sarl)

Deconvolution of ex-vivo drug screening data and bulk tissue expression predicts the abundance and viability of cancer cell subpopulations

Augmenting large language models with chemistry tools

Augmented Memory: Sample-Efficient Generative Molecular Design with Reinforcement Learning

Deconvolution of ex-vivo drug screening data and bulk tissue expression predicts the abundance and viability of cancer cell subpopulations

Augmenting large language models with chemistry tools

Augmented Memory: Sample-Efficient Generative Molecular Design with Reinforcement Learning