From the course: How AI Is Transforming Pharma: From R&D to Care Delivery

Key AI technologies in pharma and healthcare

From the course: How AI Is Transforming Pharma: From R&D to Care Delivery

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Key AI technologies in pharma and healthcare

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- Look, pharma companies know how to make drugs. That's their thing. But tech, AI, not so much. Chances are if you work in pharma right now, you aren't building AI solutions in-house, your organization is teaming up with outside vendors. But here's the catch. Even if you're outsourcing it, you still need to know how it actually works. You have to speak the language of AI. You don't need to code, but you do need to start learning the phrase book now, so you're not just nodding along in meetings. So let's start translating the common terminology. When you hear AI, you might be imagining a singular entity, but in reality, it's not just one thing. It's an umbrella term for a whole host of different technologies. Let's start with machine learning. It's AI's way of learning from a deluge of data without being programmed for specific tasks. For instance, let's say you feed it patient records. It can then predict how someone's going to react to a drug before they even take it. Super helpful when you're identifying potential drug targets. Then, we've got neural networks. These learn complex relationships, taking inspiration from the human brain. Think of them as layers of interconnected data, which represent relationships through a spider web of connections. They're great at recognizing patterns, whether it's image recognition, speech detection, or even predicting disease progression over time. That brings us to deep learning. It's especially good at making sense of dense, deeply technical data like genomic sequences. It can pick up on subtle patterns that might be hard for the human eye to detect at face value. That's the real power behind earlier diagnoses and treatments tailored to you, not just the average patient. Now, let's take that a step further, and you've got computer vision. This one's like giving AI eyes. It can look at visual data like scans or pathology slides and spot fractures, or even cancers. Doctors still call the shots, but AI is like a second opinion. Now, here's where things get even more meta, cognitive AI. It mimics how humans actually think. With perception, context, and reasoning, it can make decisions and solve problems. The best part, it learns from experience, kind of how we do. Except it's trained on something called reinforcement learning, meaning it gets better and smarter over time. It's rewarded when it gets things right. Finally, natural language processing or NLP. This one understands human language. It can scan research papers, clinical notes, or even doctor scribbles with the help of character recognition. Instead of researchers spending hours digging through documents, NLP can pull out key information and insights in a fraction of the time. Whether you're already in pharma or your goal is to move into this industry, understanding how this technology works conceptually, allows you to add more value to the conversation. It's an essential area to be familiar with as it continues to evolve pharma today.

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