When it comes to the topic of drug discovery and development, scientists are busy furrowing their lab-goggled brows trying to understand what’s real and what’s hype when it comes to the power and potential of AI.
This *Resonance Test* conversation perfectly dramatizes the situation. In this episode, Emma Eng, VP of Global Data & AI, Development at Novo Nordisk, and scientist and strategist Chris Waller provide a candid view of drug development in the AI era.
“We're standing on a revolution,” says Eng, reminding us that “we've done it so many other times” with the birth of the computer and the birth of the internet. It’s prudent, she cautions, not to rush to judgement guided by either zealots or skeptics.
Waller says, of the articles about AI and leadership in *Harvard Business Review,* one could do “a search and replace ‘AI’ with any other technological change that's happened in the last 30 years. It's the same kind of trend and processes and characteristics that you need in your leadership to implement the technology appropriately to get the outcomes that you're looking for.”
Which means, for pharma, much uncertainty and much experimentation.
“I think experimentation is good,” says Eng, who then adds that we need to always keep track of what is it that we're experimenting on. She says that the word “experimentation” can “sound very fluid” but in fact, “It's a very structured process. You set up some very clear objectives and you either prove or don't prove those objectives.”
Waller references the various revolutions (throughput screening, combinational chemistry, data, and analytics revolutions) that pharma has seen and says: “We've all held out hope for each and every one of these revolutions that the drug discovery process is going to be shrunk by 50% and cost half as much. And every time we turn around, it's still 12 to 15 years, $1.5 to $2 billion.”
Will AI make the big difference, finally?
“Maybe we need to be revolutionized as an industry,” she says. “It can be hard to make much of a difference as long as there are few big players.” Just a few big players, she says, is “the nature of pharma.”
Of course, our scientists are measured in their assessments about industry change. After all, as Waller says, the systems involved—the human body, the regulatory environment, the commercial ecosystems—are all “super-complicated.”
Eng notes that an important side-effect around the AI hype is corporate interest in data. “Now it's much easier to put that topic on the table saying, ‘If you want to do AI, you need to take care of your data and you need to treat it like an asset.’”
Listen on as they test topics such as regional and regulatory challenges in AI adoption, change management, and future tech and long-term impact (watch out for quantum, everyone!).
In the end, Eng returns to the idea of revolutions. “You think you want so much change in the beginning which you don't get because it takes time,” says Eng. This makes us underestimate what will happen later. Having such a farseeing mindset is significant, she says, because “these technology shifts will have a large impact on the long term.”
Host: Alison Kotin
Engineer: Kyp Pilalas
Producer: Ken Gordon
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When it comes to the topic of drug discovery and development, scientists are busy furrowing their lab-goggled brows trying to understand what’s real and what’s hype when it comes to the power and potential of AI.
This *Resonance Test* conversation perfectly dramatizes the situation. In this episode, Emma Eng, VP of Global Data & AI, Development at Novo Nordisk, and scientist and strategist Chris Waller provide a candid view of drug development in the AI era.
“We're standing on a revolution,” says Eng, reminding us that “we've done it so many other times” with the birth of the computer and the birth of the internet. It’s prudent, she cautions, not to rush to judgement guided by either zealots or skeptics.
Waller says, of the articles about AI and leadership in *Harvard Business Review,* one could do “a search and replace ‘AI’ with any other technological change that's happened in the last 30 years. It's the same kind of trend and processes and characteristics that you need in your leadership to implement the technology appropriately to get the outcomes that you're looking for.”
Which means, for pharma, much uncertainty and much experimentation.
“I think experimentation is good,” says Eng, who then adds that we need to always keep track of what is it that we're experimenting on. She says that the word “experimentation” can “sound very fluid” but in fact, “It's a very structured process. You set up some very clear objectives and you either prove or don't prove those objectives.”
Waller references the various revolutions (throughput screening, combinational chemistry, data, and analytics revolutions) that pharma has seen and says: “We've all held out hope for each and every one of these revolutions that the drug discovery process is going to be shrunk by 50% and cost half as much. And every time we turn around, it's still 12 to 15 years, $1.5 to $2 billion.”
Will AI make the big difference, finally?
“Maybe we need to be revolutionized as an industry,” she says. “It can be hard to make much of a difference as long as there are few big players.” Just a few big players, she says, is “the nature of pharma.”
Of course, our scientists are measured in their assessments about industry change. After all, as Waller says, the systems involved—the human body, the regulatory environment, the commercial ecosystems—are all “super-complicated.”
Eng notes that an important side-effect around the AI hype is corporate interest in data. “Now it's much easier to put that topic on the table saying, ‘If you want to do AI, you need to take care of your data and you need to treat it like an asset.’”
Listen on as they test topics such as regional and regulatory challenges in AI adoption, change management, and future tech and long-term impact (watch out for quantum, everyone!).
In the end, Eng returns to the idea of revolutions. “You think you want so much change in the beginning which you don't get because it takes time,” says Eng. This makes us underestimate what will happen later. Having such a farseeing mindset is significant, she says, because “these technology shifts will have a large impact on the long term.”
Host: Alison Kotin
Engineer: Kyp Pilalas
Producer: Ken Gordon
Silo Busting 68: Cloud IR Readiness with Ron Konigsberg, Sam Rehman & Aviv Srour
The EPAM Continuum Podcast Network
36 minutes 51 seconds
1 year ago
Silo Busting 68: Cloud IR Readiness with Ron Konigsberg, Sam Rehman & Aviv Srour
“There’s been an incident,” is a sentence no one wants to hear… except perhaps people like Ron Konigsberg, Co-Founder and CTO of Gem and our guest on *Silo Busting,* whose business is cloud incident response (IR).
We know what you’re thinking: What makes cloud IR different from all other forms of IR?
Let’s let Konigsberg explain: “The challenge is that the cloud is technically simply different.” If you’re using legacy tools, “you're going to protect probably 20% of the cloud.”
Konigsberg is joined in conversation by Sam Rehman, EPAM’s Chief Information Security Officer and SVP, and the pair are pelted with questions by Aviv Srour, our Head of Cyber Innovation.
Konigsberg says that incident responders need to “adapt from network and agents to services and APIs, and constantly learn about new services and stay up to date and up to speed” with what the bad guys are picking up.
Oh, those bad guys! Regarding attackers, Konigsberg says: “They adopt innovation faster than defenders.” They can do so because they have fewer dependencies “and they care less [than defenders do] about breaking things.”
To illustrate, he asks us to think about migrating to the cloud: Imagine you’re an attacker and you simply never worry about any legacy systems from your previous environments. “They have much more liberty and they move faster.”
“They adopt techniques about new services that each cloud provider is releasing *tomorrow,*” says Konigsberg.
So it is, in some ways, about playing catch-up. CISOs have had to adopt a new mindset and posture. “You can only block so many punches until you have to figure out [that] you need to move around, you need to counter, and so on,” says Rehman.
Rehman adds that CISOs have finally understood the “shared responsibility between you and the cloud provider.” But that’s not the only issue with the cloud. “It's much flatter than what you’re used to on prem,” he says. “Which means a lateral attack is a lot quicker, moving things around a lot easier, and the *simplicity* of people actually moving things around and infecting a large area is substantially higher.”
So how can an organization properly respond to, and learn to prioritize within, the cloud conundrum? One answer, says Rehman, is culture.
“We have to adopt a learning culture in security,” he says. “They’re always gonna be one step ahead of us, but at least we're one step behind, not ten.” Pick up the pace of your learning and listen to the experts speak. Hit play!
Host: Lisa Kocian
Editor: Kyp Pilalas
Producer: Ken Gordon
The EPAM Continuum Podcast Network
When it comes to the topic of drug discovery and development, scientists are busy furrowing their lab-goggled brows trying to understand what’s real and what’s hype when it comes to the power and potential of AI.
This *Resonance Test* conversation perfectly dramatizes the situation. In this episode, Emma Eng, VP of Global Data & AI, Development at Novo Nordisk, and scientist and strategist Chris Waller provide a candid view of drug development in the AI era.
“We're standing on a revolution,” says Eng, reminding us that “we've done it so many other times” with the birth of the computer and the birth of the internet. It’s prudent, she cautions, not to rush to judgement guided by either zealots or skeptics.
Waller says, of the articles about AI and leadership in *Harvard Business Review,* one could do “a search and replace ‘AI’ with any other technological change that's happened in the last 30 years. It's the same kind of trend and processes and characteristics that you need in your leadership to implement the technology appropriately to get the outcomes that you're looking for.”
Which means, for pharma, much uncertainty and much experimentation.
“I think experimentation is good,” says Eng, who then adds that we need to always keep track of what is it that we're experimenting on. She says that the word “experimentation” can “sound very fluid” but in fact, “It's a very structured process. You set up some very clear objectives and you either prove or don't prove those objectives.”
Waller references the various revolutions (throughput screening, combinational chemistry, data, and analytics revolutions) that pharma has seen and says: “We've all held out hope for each and every one of these revolutions that the drug discovery process is going to be shrunk by 50% and cost half as much. And every time we turn around, it's still 12 to 15 years, $1.5 to $2 billion.”
Will AI make the big difference, finally?
“Maybe we need to be revolutionized as an industry,” she says. “It can be hard to make much of a difference as long as there are few big players.” Just a few big players, she says, is “the nature of pharma.”
Of course, our scientists are measured in their assessments about industry change. After all, as Waller says, the systems involved—the human body, the regulatory environment, the commercial ecosystems—are all “super-complicated.”
Eng notes that an important side-effect around the AI hype is corporate interest in data. “Now it's much easier to put that topic on the table saying, ‘If you want to do AI, you need to take care of your data and you need to treat it like an asset.’”
Listen on as they test topics such as regional and regulatory challenges in AI adoption, change management, and future tech and long-term impact (watch out for quantum, everyone!).
In the end, Eng returns to the idea of revolutions. “You think you want so much change in the beginning which you don't get because it takes time,” says Eng. This makes us underestimate what will happen later. Having such a farseeing mindset is significant, she says, because “these technology shifts will have a large impact on the long term.”
Host: Alison Kotin
Engineer: Kyp Pilalas
Producer: Ken Gordon
