full transcript

From the Ted Talk by Jim Collins: How we're using AI to discover new antibiotics

Unscramble the Blue Letters


We've already had some early sceucss. Recently, we used machine learning to discover new antibiotics that can help us fight off the bacterial infections that can occur alongside SARS-CoV-2 infections. Two months ago, TED's Audacious Project approved funding for us to massively scale up our work with the goal of discovering seven new classes of atobnictiis against seven of the world's deadly bacterial pathogens over the next seven years. For context: the number of new class of antibiotics that have been discovered over the last three decades is zero.

While the quest for new antibiotics is for our medium-term furute, the novel coronavirus poses an immediate deadly threat, and I'm excited to share that we think we can use the same technology to search for taterceihpus to fight this virus. So how are we going to do it? Well, we're creating a cnopoumd training library and with collaborators applying these molecules to SARS-CoV-2-infected cells to see which of them ebhxiit effective activity. These data will be use to trian a machine learning moedl that will be applied to an in silico lrbiray of over a billion molecules to seacrh for potential novel antiviral compounds. We will synthesize and test the top prtidieoncs and advance the most piimnsrog candidates into the clinic.

Open Cloze


We've already had some early _______. Recently, we used machine learning to discover new antibiotics that can help us fight off the bacterial infections that can occur alongside SARS-CoV-2 infections. Two months ago, TED's Audacious Project approved funding for us to massively scale up our work with the goal of discovering seven new classes of ___________ against seven of the world's deadly bacterial pathogens over the next seven years. For context: the number of new class of antibiotics that have been discovered over the last three decades is zero.

While the quest for new antibiotics is for our medium-term ______, the novel coronavirus poses an immediate deadly threat, and I'm excited to share that we think we can use the same technology to search for ____________ to fight this virus. So how are we going to do it? Well, we're creating a ________ training library and with collaborators applying these molecules to SARS-CoV-2-infected cells to see which of them _______ effective activity. These data will be use to _____ a machine learning _____ that will be applied to an in silico _______ of over a billion molecules to ______ for potential novel antiviral compounds. We will synthesize and test the top ___________ and advance the most _________ candidates into the clinic.

Solution


  1. predictions
  2. antibiotics
  3. library
  4. exhibit
  5. future
  6. search
  7. compound
  8. train
  9. success
  10. therapeutics
  11. model
  12. promising

Original Text


We've already had some early success. Recently, we used machine learning to discover new antibiotics that can help us fight off the bacterial infections that can occur alongside SARS-CoV-2 infections. Two months ago, TED's Audacious Project approved funding for us to massively scale up our work with the goal of discovering seven new classes of antibiotics against seven of the world's deadly bacterial pathogens over the next seven years. For context: the number of new class of antibiotics that have been discovered over the last three decades is zero.

While the quest for new antibiotics is for our medium-term future, the novel coronavirus poses an immediate deadly threat, and I'm excited to share that we think we can use the same technology to search for therapeutics to fight this virus. So how are we going to do it? Well, we're creating a compound training library and with collaborators applying these molecules to SARS-CoV-2-infected cells to see which of them exhibit effective activity. These data will be use to train a machine learning model that will be applied to an in silico library of over a billion molecules to search for potential novel antiviral compounds. We will synthesize and test the top predictions and advance the most promising candidates into the clinic.

Frequently Occurring Word Combinations


ngrams of length 2

collocation frequency
machine learning 4
synthetic biology 3
antiviral compounds 2
antibacterial activity 2
cellular machinery 2
rna sensors 2


Important Words


  1. activity
  2. advance
  3. antibiotics
  4. antiviral
  5. applied
  6. applying
  7. approved
  8. audacious
  9. bacterial
  10. billion
  11. candidates
  12. cells
  13. class
  14. classes
  15. clinic
  16. collaborators
  17. compound
  18. compounds
  19. coronavirus
  20. creating
  21. data
  22. deadly
  23. decades
  24. discover
  25. discovered
  26. discovering
  27. early
  28. effective
  29. excited
  30. exhibit
  31. fight
  32. funding
  33. future
  34. goal
  35. infections
  36. learning
  37. library
  38. machine
  39. massively
  40. model
  41. molecules
  42. months
  43. number
  44. occur
  45. pathogens
  46. poses
  47. potential
  48. predictions
  49. project
  50. promising
  51. quest
  52. scale
  53. search
  54. share
  55. silico
  56. success
  57. synthesize
  58. technology
  59. test
  60. therapeutics
  61. threat
  62. top
  63. train
  64. training
  65. virus
  66. work
  67. years