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RECEPTOR.AI
Boston, United States
B
11-50 Employees
2021
Key takeaway
RECEPTOR.AI offers an AI-accelerated drug discovery platform that enhances precision and personalized medicine, focusing on selectivity among similar off-target proteins. Their end-to-end workflows are designed to address challenging drug targets, leveraging expertise in molecular biology and quantum chemistry.
Reference
Core business
AI-ACCELERATED DRUG DISCOVERY
Our flexible AI solutions are tailored to identify novel targets and design drug candidates with high success rates in clinical trials
AI|ffinity
Czechia
A
11-50 Employees
-
Key takeaway
AI|ffinity is focused on revolutionizing drug discovery through the integration of NMR, AI, and Cheminformatics. Their services, which include quantifying protein-ligand binding affinity and characterizing interactions, aim to enhance the efficiency and success rates of the early stages of drug development.
Reference
Core business
AI|ffinity - Molecular design
AIA Insights Ltd
London, United Kingdom
A
1-10 Employees
-
Key takeaway
The company emphasizes that its Drug Engine platform makes AI drug discovery techniques accessible to all scientists, fostering collaboration across various disciplines. With a focus on security and ease of use, Drug Engine aims to simplify the drug design process through AI, particularly benefiting Pharma SMEs and academics.
Reference
Core business
Drug Engine | AIA Insights
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Micar Innovation (Micar21.com)
Sofia, Bulgaria
B
1-10 Employees
2016
Key takeaway
Micar21 specializes in the entire drug discovery process, utilizing an advanced AI platform that enhances structure-based in silico drug design, significantly accelerating the identification of promising compounds for preclinical development. Their innovative approach focuses on addressing unmet medical needs and has resulted in a growing pipeline of preclinical candidates.
Reference
Core business
Micar21.com - Drug Discovery Factory - Drug Discovery faster in days
Drug Discovery Alliances
Bath, United Kingdom
A
1-10 Employees
2001
Key takeaway
Drug Discovery Alliances, Inc. specializes in pharmaceutical research and development, providing access to a global network of experts and suppliers that can enhance drug discovery efforts. Their services span the entire R&D continuum, including medicinal chemistry and cGMP API manufacturing, ensuring that they stay aligned with the latest advancements in the industry.
Reference
Product
Products - Drug Discovery Alliances, Inc.
Drug Discovery Services
IDDCR Global
Hyderabad, India
D
11-50 Employees
2007
Key takeaway
IDDCR is a leading functional service provider in the biopharma and clinical research sectors, emphasizing its commitment to integrating advanced science into drug discovery and development. Their comprehensive services include clinical research, data management, and drug safety, making them a valuable partner for pharmaceutical and biotechnology companies.
Reference
Service
Drug Discovery – IDDCR
Domainex
Cambridge, United Kingdom
A
11-50 Employees
2001
Key takeaway
The company provides comprehensive and tailored services throughout the drug discovery process, from protein expression and screening to the design and optimization of drug candidates. Their multidisciplinary team emphasizes innovation and high-quality results, establishing a strong reputation for success in the field.
Reference
Core business
Drug Discovery Services | Enrich Your Medicines Pipeline | Domainex
Glamorous AI
London, United Kingdom
A
1-10 Employees
-
Key takeaway
The company, X-Chem, utilizes advanced AI alongside DEL and medicinal chemistry to enhance small molecule drug discovery significantly. Their innovative approach positions them as leaders in the integration of AI for more effective drug development.
Reference
Core business
Artificial Intelligence For Drug Discovery | GlamorousAI | London
Artificial Intelligence For Drug Discovery | GlamorousAI | London
GVK Biosciences
Kallur, India
D
1001-5000 Employees
2001
Key takeaway
Aragen Life Sciences emphasizes its integrated approach to early-phase drug discovery, leveraging a strong scientific ecosystem that includes medicinal and computational chemists, biologists, and pharmacologists. Their commitment to delivering innovative biological solutions and accelerating the pathway to success positions them as a key partner in the AI-driven drug discovery landscape.
Reference
Product
Integrated Drug Discovery - Aragen Life Sciences
An integrated partnership approach to early phase discovery is vital to the swift and efficient progress of your molecule. Our team – comprising medicinal, synthetic and computational chemists, biologists, pharmacologists, process development and formulation scientists – offers a unified strategy to advance customer programs
ChemDiv
San Diego, United States
B
501-1000 Employees
1990
Key takeaway
ChemDiv is a global leader in drug discovery, utilizing Hybrid Artificial Intelligence (AI) and Machine Learning (ML) to enhance the drug discovery process. With a diverse collection of pharmacologically-relevant small molecules, ChemDiv has successfully delivered numerous drug candidates across various therapeutic areas.
Reference
Core business
- Chemdiv
Technologies which have been searched by others and may be interesting for you:
Artificial intelligence in drug discovery refers to the use of advanced computational techniques to streamline and optimize the process of discovering new pharmaceuticals. By leveraging machine learning algorithms and data analytics, AI can analyze vast datasets, including biological data, chemical properties, and clinical trial results, to identify potential drug candidates more efficiently than traditional methods. This technology enhances the ability to predict how different compounds will interact with biological targets, significantly reducing the time and cost associated with drug development. The integration of AI not only accelerates the identification of promising molecules but also improves the accuracy of the predictions, leading to more effective therapies being brought to market.
AI drug discovery significantly accelerates the drug development process by leveraging advanced algorithms and machine learning techniques to analyze vast datasets. This technology enables researchers to identify potential drug candidates more quickly by predicting how different compounds will interact with biological targets. Furthermore, AI can streamline the early-stage discovery phase by modeling molecular structures and simulating interactions, which reduces the time spent on traditional laboratory experiments. By automating repetitive tasks and providing insights based on data analysis, AI drug discovery not only shortens timelines but also enhances the accuracy of predictions, leading to more effective and targeted therapies being developed in a fraction of the time compared to conventional methods.
1. Enhanced Speed
Utilizing AI in drug discovery significantly accelerates the research process. Traditional methods can take years to identify potential drug candidates, while AI algorithms can analyze vast datasets and predict interactions in a fraction of the time. This rapid analysis facilitates quicker decision-making and reduces the overall time to market for new therapies.
2. Improved Accuracy
AI models leverage machine learning to identify patterns and predict outcomes with greater precision than conventional methods. By analyzing complex biological data, AI can help researchers uncover promising drug candidates that may have been overlooked. This increased accuracy not only enhances the likelihood of success in clinical trials but also minimizes the risk of late-stage failures.
AI drug discovery encounters several challenges within the healthcare industry. One significant hurdle is the integration of AI technologies with existing drug development processes. Many pharmaceutical companies rely on traditional methods, making it difficult to adopt AI solutions effectively. Additionally, data quality and availability pose critical issues. AI algorithms require vast amounts of high-quality data for training, but healthcare data can often be fragmented, incomplete, or biased. This lack of comprehensive datasets can hinder the performance of AI models, leading to less reliable outcomes in drug discovery.
AI drug discovery significantly reduces the cost of drug development by streamlining various stages of the process. By employing advanced algorithms and machine learning, AI can analyze vast datasets to identify potential drug candidates more quickly than traditional methods. This accelerates the initial phases of drug discovery, such as target identification and lead optimization, ultimately leading to faster decision-making and reduced labor costs. Furthermore, AI can predict the efficacy and safety of compounds, minimizing the risk of costly late-stage failures. By optimizing the selection of candidates for clinical trials, AI ensures that only the most promising drugs advance, which decreases the financial burden associated with extensive testing and regulatory approvals. Overall, the integration of AI technologies in drug discovery leads to a more efficient, cost-effective pipeline for developing new therapeutics.
Some interesting numbers and facts about your company results for Ai Drug Discovery
| Country with most fitting companies | United States |
| Amount of fitting manufacturers | 7983 |
| Amount of suitable service providers | 6891 |
| Average amount of employees | 11-50 |
| Oldest suiting company | 1990 |
| Youngest suiting company | 2021 |
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Some interesting questions that has been asked about the results you have just received for Ai Drug Discovery
What are related technologies to Ai Drug Discovery?
Based on our calculations related technologies to Ai Drug Discovery are Biomedical (Red), Bioinformatics (Gold), Environmental Biotechnology (Grey), Agricultural Biotechnology (Green), Food Related Biotechnology (Yellow)
Who are Start-Ups in the field of Ai Drug Discovery?
Start-Ups who are working in Ai Drug Discovery are RECEPTOR.AI
Which industries are mostly working on Ai Drug Discovery?
The most represented industries which are working in Ai Drug Discovery are IT, Software and Services, Biotechnology, Other, Pharmaceuticals, Medical
How does ensun find these Ai Drug Discovery Companies?
ensun uses an advanced search and ranking system capable of sifting through millions of companies and hundreds of millions of products and services to identify suitable matches. This is achieved by leveraging cutting-edge technologies, including Artificial Intelligence.
