Regulatory Science Virtual Symposium: “Emerging Technologies in the Medical Device Industry” Session 4: Regulatory Framework for the Digital World (2022)

1. “it's all 1s and 0s”
   1. “ASCII code” – created this table that consists of letters and numbers.
   2. L-076
   3. I-108
   4. 1-049
   5. O-079
   6. O-111
   7. 0-048
2. Only 35% trust their organizational data. 62% blame technology.
3. People vs Systems:
   1. Neurotransmitters: we think of a color, and it brings an image to our mind (e.g., magenta may make us think of flowers or magic or college).
   2. Humans are unpredictable. Unlike computers, humans change thoughts, opinions, and emotions. Computers are programmed to even act as an emotion.
4. People vs. Technology triangle: data, information, knowledge, wisdom
   1. Data
      • i.      People aren’t good with tedious tasks, but computers are great. Data Integrity (Alcoa-attributable, legible, contemporaneous, original, and complete): made up in the industry by some guy who was nervous to give speeches and needed to remember something and took Alcoa to do that/ made him think of a company name…now we live by it. all of us have used tech for most of our lives.
      • ii.      System perspective/ Information: systems don’t have perspective; created by people that have perspective who may miscommunicate. We human beings must validate everything to ensure consistent performance.
      • iii.      Hybrid Perspective/wisdom and knowledge: humans are taught perspective, knowledge and wisdom, opinions, etc.
      • iv.      We use what we know to plug it into the systems and that’s how it is run.
      • v.      Need critical thinking and an open mind to consider a basic understanding to develop a system appropriately.
5. Artificial intelligence:
   1. When a machine displays some human-like intelligence (e.g., Alexa from amazon, Sofia the robot [has citizenship in Saudi Arabia, which holds ethical dilemmas], Software robots [bots])
      • i.      Artificial general intelligence: Homo Deus by Yuval (wrote Sapiens).
        1. All our jobs can be replaced by technology. Archaeology and creation of virtual worlds.
        2. There are systems that diagnose patients better than doctors (surgery robots). Eventually, the systems will start thinking for themselves.
        3. In the middle of our fourth industrial revolution: steam, electronics, robot, and cyber-physical systems (human and technology working and coming together).
        4. In a pharmaceutical factory, devices will be figuring out problems themselves…they will be proactive and predictive. It will find a problem and know how to fix it.
      • ii.      Sentiment analysis: the system can tell how you are based on facial expressions.
        1. System can communicate with physicians to tell them the truth behind a patient’s emotions.
      • iii.      Tech will never replace humans. It will only work together with humans to improve our quality of life.
6. Machine Learning:
   1. Automating analytical model building.
   2. With machine learning, we can throw heaps and mounds of data and see you had something good; you just didn’t see it. Plenty of archives for new drugs; just need the extra help.
      • i.      Supervised Learning: trained the machine to find something specific
      • ii.      Semi-supervised learning
      • iii.      Unsupervised learning: throwing data at the machine that it knows nothing about.
   3. Machine interprets whether it sees a cat or a dog.

Accompanying text created by Roxy Terteryan | RKS Project Administrator, SC CTSI  atertery@usc.edu