For medical imaging technology, AI time has already arrived. Seven years ago, there were almost no AI-enabled devices being approved. Since then, they’ve grown roughly in a straight line. Now about 40% of all radiology devices being approved are AI enabled, as the first chart below shows. As a result, sales of AI diagnostic devices are likely to grow rapidly. The consensus forecast is for 33% compound growth over the next five years. This means there’s a big opportunity for start-ups and established players. In some areas, AI has now become a necessary cost of doing business. In others it is possible to carve out a niche providing AI as a service particularly when serving the BioPharma industry. The path won’t be completely smooth, however, according to the CGI report, because many doctors are reluctant to embrace AI-enabled devices. The full report has more on that. AI-enabled devices as a % of all radiology devices approved by the FDA Source: FDA Predictability of Reimbursement for Digital Devices Source: BCG and UCLA Biobank The FDA has tried to encourage innovation, and as a result AI-driven devices are now typically launched in the U.S. By contrast the EU’s new safety-first approach has made it much harder to introduce products there. Many companies now say they will delay their European launches, if they do so at all. In the U.S. the most important barrier to the use of new types of medical devices now revolves around “reimbursement” rather than “approval”. The FDA, or its equivalents overseas, may approve an AI-enabled device, but health providers will buy it only if they believe payers will reimburse its use. Unfortunately, the second chart above shows companies find it extremely hard to predict whether there will be reimbursement for new digital medical devices, both in the U.S. and in Europe. Despite these issues, however, AI-enabled medical devices are growing rapidly – which means MedTech is likely to be the first area within health where AI will have a significant impact. The number of AI-enabled medical devices approved by the FDA has grown steadily, as the first chart below shows, from close to zero before 2015 to 72 in 2H21 (the last six-month period we have full data for). The growth is impressive, and there is no sign that the rate increase will slow down. However it’s important to put it in context: the second chart below shows that AI-enabled devices still represent only about 5% of all Class II medical devices being approved. Figure 7. Number of AI devices approved by FDA (# per 6-month period) Source: FDA Figure 8. AI-enabled device approvals as a % of all FDA Class II approvals Source: FDA About three quarters of all the AI products that have been approved are in radiology, in other words in medical imaging, with cardiovascular devices a distant second. Almost 90% of those radiology devices are for diagnosis and that the main techniques in the field – CT, Ultrasound, MRI, X-Ray – are all well represented. Only 11% of AI-enabled radiology devices are dedicated to the therapeutic side of radiology – which typically involves using radiation to kill cancer cells, often in the earlier stages of cancer. The full report looks in greater depth at how AI is being monetized in healthcare and covers several examples and case studies of AI in action across the sector. To read it in full, if you are a Velocity subscriber, please see Smart Thinking on AI in Healthcare: Part 2 – Medical Devices: AI is increasingly disrupting radiology (6 April) Citi Global Insights (CGI) is Citi’s premier non-independent thought leadership curation. It is not investment research; however, it may contain thematic content previously expressed in an Independent Research report. For the full CGI disclosure, click here.

For medical imaging technology, AI time has already arrived. &nbsp;
Seven years ago, there were almost no AI-enabled devices being approved. Since then, they&rsquo;ve grown roughly in a straight line. Now about 40% of all radiology devices being approved are AI enabled, as the first chart below shows.
As a result, sales of AI diagnostic devices are likely to grow rapidly. The consensus forecast is for 33% compound growth over the next five years.
This means there&rsquo;s a big opportunity for start-ups and established players. In some areas, AI has now become a necessary cost of doing business. In others it is possible to carve out a niche providing AI as a service particularly when serving the BioPharma industry.
The path won&rsquo;t be completely smooth, however, according to the CGI report, because many doctors are reluctant to embrace AI-enabled devices. The full report has more on that.
&nbsp;
AI-enabled devices as a % of all radiology devices approved by the FDA
<img src="/rcs/v1/media/citigpa/akpublic/storage/retrieveMediaFile/64808d2c8c88e95cfe692602.png" width="514" height="345" />
Source: FDA
&nbsp;
Predictability of Reimbursement for Digital Devices 
<img src="/rcs/v1/media/citigpa/akpublic/storage/retrieveMediaFile/64808d89ef207e3f74ade3d0.png" />
Source: BCG and UCLA Biobank 
&nbsp;
The FDA has tried to encourage innovation, and as a result AI-driven devices are now typically launched in the U.S.
By contrast the EU&rsquo;s new safety-first approach has made it much harder to introduce products there. Many companies now say they will delay their European launches, if they do so at all.
In the U.S. the most important barrier to the use of new types of medical devices now revolves around &ldquo;reimbursement&rdquo; rather than &ldquo;approval&rdquo;. The FDA, or its equivalents overseas, may approve an AI-enabled device, but health providers will buy it only if they believe payers will reimburse its use. Unfortunately, the second chart above shows companies find it extremely hard to predict whether there will be reimbursement for new digital medical devices, both in the U.S. and in Europe. &nbsp;
Despite these issues, however, AI-enabled medical devices are growing rapidly &ndash; which means MedTech is likely to be the first area within health where AI will have a significant impact.&nbsp;
The number of AI-enabled medical devices approved by the FDA has grown steadily, as the first chart below shows, from close to zero before 2015 to 72 in 2H21 (the last six-month period we have full data for).
The growth is impressive, and there is no sign that the rate increase will slow down. However it&rsquo;s important to put it in context: the second chart below shows that AI-enabled devices still represent only about 5% of all Class II medical devices being approved.
&nbsp;
Figure 7. Number of AI devices approved by FDA (# per 6-month period)
<img src="/rcs/v1/media/citigpa/akpublic/storage/retrieveMediaFile/64808e02ef207e3f74ade3d3.png" />
Source: FDA
&nbsp;
Figure 8. AI-enabled device approvals as a % of all FDA Class II approvals
<img src="/rcs/v1/media/citigpa/akpublic/storage/retrieveMediaFile/64808e38141fa96b32804303.png" />
Source: FDA
&nbsp;
About three quarters of all the AI products that have been approved are in radiology, in other words in medical imaging, with cardiovascular devices a distant second.
Almost 90% of those radiology devices are for diagnosis and that the main techniques in the field &ndash; CT, Ultrasound, MRI, X-Ray &ndash; are all well represented. Only 11% of AI-enabled radiology devices are dedicated to the therapeutic side of radiology &ndash; which typically involves using radiation to kill cancer cells, often in the earlier stages of cancer.
The full report looks in greater depth at how AI is being monetized in healthcare and covers several examples and case studies of AI in action across the sector.
To read it in full, if you are a Velocity subscriber, please see <a href="https://www.citivelocity.com/t/r/eppublic/2iauM" target="_blank" rel="noopener" data-link-source="tiny">Smart Thinking on AI in Healthcare: Part 2 &ndash; Medical Devices: AI is increasingly disrupting radiology</a> (6 April)
Citi Global Insights (CGI) is Citi&rsquo;s premier non-independent thought leadership curation. It is not investment research; however, it may contain thematic content previously expressed in an Independent Research report. For the full CGI disclosure, click <a href="https://ir.citi.com/6A3IURUaezPxFLppsgdBkqidjLaLn558JwHISYaDZcTfE9XMRB1isDDDVorqrxpR%2fTnEi4RUCl8%3d" target="_blank" rel="noopener" data-link-source="tiny">here</a>.
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A recent report by Adam Spielman of Citi Global Insights the second in a series on AI in healthcare looks at how AI is already having an impact on medical devices, and in particular on radiology and imaging. 

AI in Healthcare: Medical Devices 

Administration is a part of healthcare that’s often underappreciated by outsiders. It’s also currently very inefficient and therefore ripe for disruption by AI. Here’s why it’s important: Excessive cost: Very roughly one-quarter of all spending on healthcare in the US is on administrative tasks, but automation could save perhaps 25-30% of this. Burden on clinicians: Burnout is an increasing problem in many health systems globally, including in the US, and more than 90% of clinicians say excessive admin is contributing to burnout. Industry fragmentation: Friction in the flow of information means the healthcare system is currently split into distinct entities, e.g., the providers, payers, and government, with little integration among them, and misaligned incentives. “It’s easy to think that sorting out health admin isn’t that sexy,” according to Dr. Avi Mehra, a co-founder of Doctorpreneurs and CSO in IBM’s health tech team. “But there will probably be more improvement in healthcare provision, for less effort by applying AI to health administration, relative to the clinical side.” Healthcare Industry -- Fragmentation and Consolidation © 2023 Citigroup Inc. No redistribution without Citigroup’s written permission. Source: Deloitte Consulting, Citi Global Insights AI is already starting to help automate a great deal, and the authors believe that the advent of really good understanding of ordinary language will accelerate this. “AI presents a large opportunity to help reduce bottlenecks and automate several areas of health admin,” says Elliot Jenks, a managing director at Citi’s investment bank, responsible for health services. “That means you could make a lot of processes much more efficient and lower cost.” The authors also believe that, in the future, faster information flows among the various parts of the healthcare system will mean they will become more integrated, focusing more and more on the benefits for the consumer. It is hard to overstate just how burdensome administration is for clinicians. There is unprecedented stress among clinicians following Covid, and poor, disconnected IT is a major factor: “Clinicians are spending too much time working on admin tasks like pre-authorization scheduling and answering prescription questions that could be automated," says Morgann Carlon, a Health AI leader at Deloitte. According to one survey of US clinicians: 92% of clinicians agree that admin is a major contributor to healthcare worker burnout. 36% of clinicians spend more than half their time on administration. The full report goes on to discuss several other areas, including ambient administration in which a smart AI assistant could listen to the conversation between patient and doctor with the AI behind it and help extract relevant information. It also looks at how AI could improve care for patients, as it can effectively triage, organize, and deliver care to those most in need. For more information on this subject, and if you are a Velocity subscriber, please see the full report, published on 25 April 2023, here: https://www.citivelocity.com/ And here are the previous reports in this series: Smart Thinking on AI in Healthcare: Part 1 – Overview Smart Thinking on AI in Healthcare: Part 2 – Medical Devices Citi Global Insights (CGI) is Citi’s premier non-independent thought leadership curation. It is not investment research; however, it may contain thematic content previously expressed in an Independent Research report. For the full CGI disclosure, click here.

&nbsp;
Administration is a part of healthcare that&rsquo;s often underappreciated by outsiders. It&rsquo;s also currently very inefficient and therefore ripe for disruption by AI. Here&rsquo;s why it&rsquo;s important:
<ul>
<li>Excessive cost: Very roughly one-quarter of all spending on healthcare in the US is on administrative tasks, but automation could save perhaps 25-30% of this.</li>
</ul>
<ul>
<li>Burden on clinicians: Burnout is an increasing problem in many health systems globally, including in the US, and more than 90% of clinicians say excessive admin is contributing to burnout.</li>
</ul>
<ul>
<li>Industry fragmentation: Friction in the flow of information means the healthcare system is currently split into distinct entities, e.g., the providers, payers, and government, with little integration among them, and misaligned incentives.&nbsp;</li>
</ul>
&ldquo;It&rsquo;s easy to think that sorting out health admin isn&rsquo;t that sexy,&rdquo; according to Dr. Avi Mehra, a co-founder of Doctorpreneurs and CSO in IBM&rsquo;s health tech team. &ldquo;But there will probably be more improvement in healthcare provision, for less effort by applying AI to health administration, relative to the clinical side.&rdquo;
Healthcare Industry -- Fragmentation and Consolidation
<img src="/rcs/v1/media/citigpa/akpublic/storage/retrieveMediaFile/64ef5e7f860feb324c9fed50.png" width="711" height="413" />
&copy; 2023 Citigroup Inc. No redistribution without Citigroup&rsquo;s written permission.
Source: Deloitte Consulting, Citi Global Insights
AI is already starting to help automate a great deal, and the authors believe that the advent of really good understanding of ordinary language will accelerate this.
&ldquo;AI presents a large opportunity to help reduce bottlenecks and automate several areas of health admin,&rdquo; says Elliot Jenks, a managing director at Citi&rsquo;s investment bank, responsible for health services. &ldquo;That means you could make a lot of processes much more efficient and lower cost.&rdquo;&nbsp;
The authors also believe that, in the future, faster information flows among the various parts of the healthcare system will mean they will become more integrated, focusing more and more on the benefits for the consumer.
It is hard to overstate just how burdensome administration is for clinicians. There is unprecedented stress among clinicians following Covid, and poor, disconnected IT is a major factor:
&ldquo;Clinicians are spending too much time working on admin tasks like pre-authorization scheduling and answering prescription questions that could be automated," says Morgann Carlon, a Health AI leader at Deloitte.
According to one survey of US clinicians:
<ul>
<li>92% of clinicians agree that admin is a major contributor to healthcare worker burnout.</li>
</ul>
<ul>
<li>36% of clinicians spend more than half their time on administration.</li>
</ul>
The full report goes on to discuss several other areas, including ambient administration in which a smart AI assistant could listen to the conversation between patient and doctor with the AI behind it and help extract relevant information. It also looks at how AI could improve care for patients, as it can effectively triage, organize, and deliver care to those most in need.&nbsp;
For more information on this subject, and if you are a Velocity subscriber, please see the full report, published on 25 April 2023, here: <a href="https://www.citivelocity.com/" target="_blank" rel="noopener" data-link-source="tiny">https://www.citivelocity.com/</a>
And here are the previous reports in this series: 
 <a href="https://www.citivelocity.com/rendition/eppublic/public/documentService/ZG9jX2lkPTMwMTQzMjE5" target="_blank" rel="noopener" data-link-source="tiny">Smart Thinking on AI in Healthcare: Part 1 &ndash; Overview</a> 
<a href="https://www.citivelocity.com/rendition/eppublic/public/documentService/ZG9jX2lkPTMwMTQ1MjEz" target="_blank" rel="noopener" data-link-source="tiny">Smart Thinking on AI in Healthcare: Part 2 &ndash; Medical Devices</a> 
Citi Global Insights (CGI) is Citi&rsquo;s premier non-independent thought leadership curation. It is not investment research; however, it may contain thematic content previously expressed in an Independent Research report. For the full CGI disclosure, click <a href="https://ir.citi.com/6A3IURUaezPxFLppsgdBkqidjLaLn558JwHISYaDZcTfE9XMRB1isDDDVorqrxpR%2fTnEi4RUCl8%3d" target="_blank" rel="noopener" data-link-source="tiny">here</a>.

A recent report from Adam Spielman of Citi Global Insights looks at the possibilities for AI to impact health administration, potentially cutting costs and helping ease the huge burden on clinicians. 

AI in Healthcare: Health Administration 

He says that: AI is especially important for biopharma, because AI can understand biology in a way that humans cannot; and Biopharma is in a particularly strong position to adopt AI, because it is simultaneously highly profitable and extremely inefficient (given the iterative trial and error approach towards drug discovery). Here’s a bit more on each of those points. 1. AI is especially important for biopharma The reason AI is likely to have such a profound impact in biopharma is that the same sort of transformer technology that can (sort of) understand natural languages like English can also be applied to long molecules like proteins and RNA. Humans understand and can manipulate English better than AI can; by contrast the way molecules work is not intuitive to humans. As a result, it’s fair to say that in many ways AI understands the language of large bio-molecules better than humans do. One sign of AI’s power to change biopharma is that several of the individuals who have been at the cutting edge of AI are now focusing on using AI to accelerate the development of drugs – for example, Demis Hassabis (the founder and CEO of DeepMind) and Daphne Koller (a former professor of computer science at Stanford). Another indication is that of all the academic papers on AI, the ones that have been most cited in the past couple of years have actually focused on proteins. 2. Biopharma is also in a very strong position to adopt AI Biopharma operates a business model quite unlike any other industry, and many of the peculiarities seem tailor-made to adopting AI: Lots of cash to invest in AI. When drugs are approved they operate as quasi- monopolies, with very high margins. This means both that many pharma companies have strong cash flows, and that there are huge levels of R&D investment in the biopharma sector. There is plenty of scope for AI to bring improvements because the industry involves extraordinary inefficiencies. Developing new drugs often takes 15 years and costs billions of dollars. Typically, thousands of molecules are tested before one is taken to clinical trials – but even then 92% of the candidate drugs fail in clinical trials. For those drugs that succeed, it takes an average of more than a decade from the start of clinical trials to approval. And time is of the essence. Biotech companies have to file patents on their drugs before they start clinical trials, and the patents last for only 20 years, at least in theory. Even though they are often extended in practice, pharma companies have only a limited number of years to generate returns from the drugs. Anything that can bring drugs to market faster is therefore likely to have a major economic impact – and there is plenty of evidence that AI should be able to do that. AI is likely to improve the industry’s cashflow: New drugs can generate revenues in the billions. If AI allows new drugs to be found – to drug the previously undruggable – then the upside could potentially be worth billions of dollars. Bringing drugs to market faster can improve cash flows very substantially. AI can produce drugs more quickly, which means the drug is likely to produce revenue for a greater percentage of the patent period. Accelerating approval by 12 months can increase the NPV of a drug by $100 million. Better drugs can generate higher revenues. AI-designed drugs have the potential for greater revenue, even if they are treating diseases where therapies already exist, because they can be targeted more tightly and designed with fewer side effects. AI can reduce the cost of development substantially, especially in the discovery phase. Exscientia says AI-driven drug development can reduce the costs in the preclinical phases by about 70%, relative to traditional techniques. Biopharma is the largest subsector within healthcare in economic terms One reason why the impact of AI on biopharma is important is that it is the dominant subsector of healthcare in financial terms. Biopharma accounts for very roughly half of the industry’s profit and investment, even though prescription drugs account for only 11% of spending on healthcare in the US (see first chart below). The second chart below shows that over the last two years, $102 billion was invested in biotech and drug start-ups, and a further $7 billion was invested in tools for drug discovery, together making up 48% of total investment by VCs in healthcare. US Healthcare Spend by Category, 2021 Source: CMS Primary Capital Raised in Healthcare Startups, 2021 and 2022 combined ($ in Blns) Source: PitchBook The full report goes on to look at companies that are using AI in biopharma. Colleagues in Citi Global Data Insights (CGDI) are able to respond to requests to generate screens of companies exposed to the themes in this report, based on a quantitative analysis both of patents filed and of newsflow. These screens can cover quoted and unquoted companies. They can be ranked in many ways. For example, it is possible to rank by the number of patents obtained related to AI in biopharma, or the quality of those patents, or the percentage of a company’s patents that fall in this area. Please reach out to the author (adam.spielman@citi.com) or to Helen Krause (helen.krause@citi.com) at CGDI for more information on any of this. Please find the full report here, originally published on 23 June 2023, and if you are a Velocity subscriber: https://www.citivelocity.com/ And please find the previous reports in the series here: Smart Thinking on AI in Healthcare: Part 1 – Overview Smart Thinking on AI in Healthcare: Part 2 – Medical Devices Smart Thinking on AI in Healthcare: Part 3 – Health Administration Citi Global Insights (CGI) is Citi’s premier non-independent thought leadership curation. It is not investment research; however, it may contain thematic content previously expressed in an Independent Research report. For the full CGI disclosure, click here.

He says that:
<ul>
<li>AI is especially important for biopharma, because AI can understand biology in a way that humans cannot; and</li>
</ul>
<ul>
<li>Biopharma is in a particularly strong position to adopt AI, because it is simultaneously highly profitable and extremely inefficient (given the iterative trial and error approach towards drug discovery).</li>
</ul>
Here&rsquo;s a bit more on each of those points.
1. AI is especially important for biopharma
The reason AI is likely to have such a profound impact in biopharma is that the same sort of transformer technology that can (sort of) understand natural languages like English can also be applied to long molecules like proteins and RNA. Humans understand and can manipulate English better than AI can; by contrast the way molecules work is not intuitive to humans. As a result, it&rsquo;s fair to say that in many ways AI understands the language of large bio-molecules better than humans do.
One sign of AI&rsquo;s power to change biopharma is that several of the individuals who have been at the cutting edge of AI are now focusing on using AI to accelerate the development of drugs &ndash; for example, Demis Hassabis (the founder and CEO of DeepMind) and Daphne Koller (a former professor of computer science at Stanford).
Another indication is that of all the academic papers on AI, the ones that have been most cited in the past couple of years have actually focused on proteins. &nbsp;&nbsp;
2. Biopharma is also in a very strong position to adopt AI
Biopharma operates a business model quite unlike any other industry, and many of the peculiarities seem tailor-made to adopting AI:
<ul>
<li>Lots of cash to invest in AI. When drugs are approved they operate as quasi- monopolies, with very high margins. This means both that many pharma companies have strong cash flows, and that there are huge levels of R&amp;D investment in the biopharma sector.</li>
</ul>
<ul>
<li>There is plenty of scope for AI to bring improvements because the industry involves extraordinary inefficiencies. Developing new drugs often takes 15 years and costs billions of dollars. Typically, thousands of molecules are tested before one is taken to clinical trials &ndash; but even then 92% of the candidate drugs fail in clinical trials. For those drugs that succeed, it takes an average of more than a decade from the start of clinical trials to approval. </li>
</ul>
<ul>
<li>And time is of the essence. Biotech companies have to file patents on their drugs before they start clinical trials, and the patents last for only 20 years, at least in theory. Even though they are often extended in practice, pharma companies have only a limited number of years to generate returns from the drugs. Anything that can bring drugs to market faster is therefore likely to have a major economic impact &ndash; and there is plenty of evidence that AI should be able to do that.</li>
</ul>
AI is likely to improve the industry&rsquo;s cashflow:
<ul>
<li>New drugs can generate revenues in the billions. If AI allows new drugs to be found &ndash; to drug the previously undruggable &ndash; then the upside could potentially be worth billions of dollars.</li>
</ul>
<ul>
<li>Bringing drugs to market faster can improve cash flows very substantially. AI can produce drugs more quickly, which means the drug is likely to produce revenue for a greater percentage of the patent period. Accelerating approval by 12 months can increase the NPV of a drug by $100 million.</li>
</ul>
<ul>
<li>Better drugs can generate higher revenues. AI-designed drugs have the potential for greater revenue, even if they are treating diseases where therapies already exist, because they can be targeted more tightly and designed with fewer side effects.</li>
</ul>
AI can reduce the cost of development substantially, especially in the discovery phase. Exscientia says AI-driven drug development can reduce the costs in the preclinical phases by about 70%, relative to traditional techniques.
<h1>Biopharma is the largest subsector within healthcare in economic terms</h1>
One reason why the impact of AI on biopharma is important is that it is the dominant subsector of healthcare in financial terms. Biopharma accounts for very roughly half of the industry&rsquo;s profit and investment, even though prescription drugs account for only 11% of spending on healthcare in the US (see first chart below).
The second chart below shows that over the last two years, $102 billion was invested in biotech and drug start-ups, and a further $7 billion was invested in tools for drug discovery, together making up 48% of total investment by VCs in healthcare.
US Healthcare Spend by Category, 2021
<img src="/rcs/v1/media/citigpa/akpublic/storage/retrieveMediaFile/64ef6343860feb324c9fed5c.png" width="630" height="434" />
Source: CMS 
Primary Capital Raised in Healthcare Startups, 2021 and 2022 combined ($ in Blns) 
<img src="/rcs/v1/media/citigpa/akpublic/storage/retrieveMediaFile/64ef63a4daa69a4e782489ef.png" width="631" height="420" />
Source: PitchBook
The full report goes on to look at companies that are using AI in biopharma. Colleagues in Citi Global Data Insights (CGDI) are able to respond to requests to generate screens of companies exposed to the themes in this report, based on a quantitative analysis both of patents filed and of newsflow.
These screens can cover quoted and unquoted companies. They can be ranked in many ways. For example, it is possible to rank by the number of patents obtained related to AI in biopharma, or the quality of those patents, or the percentage of a company&rsquo;s patents that fall in this area.
Please reach out to the author (<a href="mailto:adam.spielman@citi.com" target="_blank" rel="noopener" data-link-source="tiny">adam.spielman@citi.com</a>) or to Helen Krause (<a href="mailto:helen.krause@citi.com" target="_blank" rel="noopener" data-link-source="tiny">helen.krause@citi.com</a>) at CGDI for more information on any of this.
Please find the full report here, originally published on 23 June 2023, and if you are a Velocity subscriber: <a href="https://www.citivelocity.com/" target="_blank" rel="noopener" data-link-source="tiny">https://www.citivelocity.com/</a>
And please find the previous reports in the series here:
<a href="https://www.citivelocity.com/rendition/eppublic/public/documentService/ZG9jX2lkPTMwMTQzMjE5" target="_blank" rel="noopener" data-link-source="tiny">Smart Thinking on AI in Healthcare: Part 1 &ndash; Overview</a> 
<a href="https://www.citivelocity.com/rendition/eppublic/public/documentService/ZG9jX2lkPTMwMTQ1MjEz" target="_blank" rel="noopener" data-link-source="tiny">Smart Thinking on AI in Healthcare: Part 2 &ndash; Medical Devices</a> 
<a href="https://www.citivelocity.com/rendition/eppublic/public/documentService/ZG9jX2lkPTMwMTQ4MjY0" target="_blank" rel="noopener" data-link-source="tiny">Smart Thinking on AI in Healthcare: Part 3 &ndash; Health Administration</a> 
Citi Global Insights (CGI) is Citi&rsquo;s premier non-independent thought leadership curation. It is not investment research; however, it may contain thematic content previously expressed in an Independent Research report. For the full CGI disclosure, click <a href="https://ir.citi.com/6A3IURUaezPxFLppsgdBkqidjLaLn558JwHISYaDZcTfE9XMRB1isDDDVorqrxpR%2fTnEi4RUCl8%3d" target="_blank" rel="noopener" data-link-source="tiny">here</a>.

A recent report from Adam Spielman of Citi Global Insights looks at biopharma and why AI is especially important in this area. He says biopharma will be affected by AI more than any other aspect of the healthcare industry. In fact, he says it will be affected more than almost any other industry. 

AI in Healthcare: The Importance of Biopharma 

Interview with CEO of IonQ – Peter Chapman, discussion includes: Why is the healthcare sector expected to benefit immensely from quantum computing? Could quantum computers enable a new era of simulation-based drug discovery? Can quantum computers help develop better vaccines? Could quantum computers enable better and more cost-efficient diagnoses? What are some of the biggest challenges in the healthcare sector that quantum computing could help overcome?

Interview with CEO of IonQ &ndash; Peter Chapman, discussion includes:
<ul type="square">
<li>Why is the healthcare sector expected to benefit immensely from quantum computing?</li>
<li>Could quantum computers enable a new era of simulation-based drug discovery?</li>
<li>Can quantum computers help develop better vaccines?</li>
<li>Could quantum computers enable better and more cost-efficient diagnoses?</li>
<li>What are some of the biggest challenges in the healthcare sector that quantum computing could help overcome?</li>
</ul>