CHEMISTRY LAB ROBOTICS

 

IBM RXN https://rxn.app.accelerate.science/rxn/robo-rxn/welcome

 

IBM RXN TUTORIAL https://www.youtube.com/watch?v=UTGR3E5u7s0

 

 

EXAMPLES OF AUTOMATED LABS:

 

1. Syngenta: Syngenta is using AI to design new pesticides that are more effective and less harmful to the environment. Website: Syngenta

2. Bayer: Bayer is using ML to predict the properties of new drug candidates to develop drugs more quickly and efficiently. Website: Bayer

3. Dow: Dow is using robotics to synthesize and test new materials for various industries, including packaging, construction, and electronics. Website: Dow

4. BASF: BASF is using AI to design new catalysts to speed up chemical reactions. Website: BASF

5. DSM: DSM is using ML to predict the performance of new food products, making them healthier and more sustainable. Website: DSM

6. Evotec: Evotec is using robotics to screen large compound libraries for potential new drug candidates. Website: Evotec

7. Exscientia: Exscientia is using AI to design and synthesize new drug candidates, which they test in clinical trials. Website: Exscientia

8. BenevolentAI: BenevolentAI is using AI to identify new drug targets and design drugs that target those targets. Website: BenevolentAI

9. Insilico Medicine: Insilico Medicine is using AI to simulate the behavior of cells and tissues to develop new drugs and predict drug toxicity. Website: Insilico Medicine

10. Atomwise: Atomwise is using AI to identify new drug candidates by screening large databases of molecules. Website: Atomwise

11. Helix Therapeutics: Helix Therapeutics is using AI to design new DNA sequences that encode proteins with desired properties. Website: Helix Therapeutics

12. Recursion Pharmaceuticals: Recursion Pharmaceuticals is using AI to analyze large datasets of biological and chemical data to identify new drug targets and design drugs targeting those targets. Website: Recursion Pharmaceuticals

 

 

PROGRAMMING CHEMISTRY LAB ROBOTS

 

• Programming languages:

  • Python tutorials: https://www.w3schools.com/python/

  • C++ tutorials: https://cplusplus.com/doc/tutorial/

  • Java tutorials: https://www.w3schools.com/java/

  • RPA tutorial https://www.javatpoint.com/rpa

• Robotics:

  • Robotics: Modelling, Planning and Control: https://www.amazon.com/Robotics-Modelling-Planning-Textbooks-Processing/dp/1846286417

  • Probabilistic Robotics: http://www.probabilistic-robotics.org/

  • Robot Operating System (ROS) tutorials: http://wiki.ros.org/ROS/Tutorials

• Chemistry:

  • Chemistry: The Central Science: https://www.amazon.com/Chemistry-Central-Science-Books-Carte/dp/0134555635

  • General Chemistry: https://en.wikipedia.org/wiki/General_chemistry

  • Organic Chemistry: https://en.wikipedia.org/wiki/Organic_chemistry

• Lab automation techniques:

  • Laboratory Automation: https://en.wikipedia.org/wiki/Laboratory_automation

  • Automated Laboratory Systems: https://study.com/learn/lesson/laboratory-automation-types-equipment.html

  • Robotics in the Laboratory: https://en.wikipedia.org/wiki/Laboratory_robotics

• Computer vision:

  • Computer Vision: A Modern Approach: https://www.amazon.com/Computer-Vision-Modern-Approach-2nd/dp/013608592X

  • OpenCV: https://opencv.org/

  • PyTorch: https://pytorch.org/

• Natural language processing:

  • Natural Language Processing: https://www.ibm.com/topics/natural-language-processing

  • spaCy: https://spacy.io/

  • Hugging Face Transformers:https://huggingface.co/transformers/

• Machine learning:

  • Machine Learning in Action: https://www.manning.com/books/machine-learning-in-action

  • scikit-learn: https://scikit-learn.org/

  • TensorFlow: https://www.tensorflow.org/