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The Promise of Comprehensive Genomic Profiling in the USA by EOS Intelligence
by EOS Intelligence EOS Intelligence No Comments

The Promise of Comprehensive Genomic Profiling in the USA

Comprehensive Genomic Profiling (CGP) is a diagnostic tool that sequences a patient’s tumor DNA to identify genetic mutations that drive cancer growth. Insurance coverage for CGP varies widely depending on the type of cancer, the patient’s stage of disease, and the specific test being used.  Despite CGP’s tremendous potential to transform cancer care and diagnosis, its implementation is hindered by inconsistent insurance coverage policies.

Comprehensive genomic profiling is a cutting-edge technology that is revolutionizing cancer diagnosis and treatment. Unlike standard gene testing, which looks at a small number of genes, CGP analyzes thousands of genes across the entire genome. This provides a much more comprehensive picture of genetic mutations that may be driving a patient’s cancer, thereby leading to more personalized and effective treatment options. Despite the benefits of CGP, access to this technology remains limited due to a variety of factors, which include high costs, limited insurance coverage, and regulatory hurdles.

One of the biggest challenges for CGP has been payer acceptability. Payers tend to be cautious about covering CGP because it is a relatively new technology, and there is still some debate about its clinical value and cost-effectiveness.

Private payers in the USA are more likely to cover CGP for patients with rare or complex cancers or for patients who have failed standard therapies, such as chemotherapy or radiation therapy.

In contrast, public payers, such as Medicare, may have more restrictive criteria for coverage and only cover CGP for certain types of cancer or for patients who meet specific clinical criteria. These criteria could include a requirement that CGP tests be performed in Medicare-accredited labs. Other major public payers in the USA, such as Medicaid and Veterans Affairs (VA) health plans, also cover CGP, but each payer has different criteria for coverage. Generally, they require that the test is ordered by a physician and is deemed medically necessary for the patient’s treatment plan.

The lack of coverage makes it financially inaccessible for many patients, which limits the ability of healthcare providers to consistently offer CGP testing. This presents a significant obstacle to the widespread adoption of this promising diagnostic tool. Some payers are hesitant to reimburse CGP due to concerns about the cost-effectiveness of the test and the lack of long-term data on clinical outcomes. However, major public and private payers such as Medicare, UnitedHealth (UHC), Aetna, and Cigna, among others, have included CGP tests in their health policies in recent years, nonetheless, the coverage remains uneven.

Cost and regulatory hurdles are stifling the growth of CGP

Payers have historically covered traditional testing, such as immunohistochemistry (IHC), fluorescent in situ hybridization (FISH), and single gene tests, but have been hesitant to provide coverage for CGP. This is mainly because these tests have been around for longer than CGP, so payers are more familiar with them and are more comfortable covering them.

Another reason is that CGP is more expensive than traditional tests. While the exact cost varies depending on the specific test and lab performing it, the cost of CGP tests can range from a few hundred dollars to several thousand dollars, while traditional tests are typically in the range of a few hundred dollars. This is due to the fact that CGP tests are more complex as they analyze a large number of genes, whereas traditional tests focus on analyzing one specific gene at a time, making them less expensive.

According to a study published in 2021 by the Journal of Clinical Oncology, CGP could improve overall survival by about 6% (0.06 years, a relatively small but meaningful amount of time for cancer patients and their families) for US$9,000 per patient, compared with traditional testing strategies. On the other hand, as per a 2022 article by the American Journal of Managed Care, although the cost of CGP tests is high, these tests can help identify the most effective treatment options for each patient, which can lead to better outcomes and fewer unnecessary treatments, which in turn can lower overall healthcare costs.

Read our related Perspective:
 Commentary: Genetic Testing Fraud – The Next Big Concern for the US Healthcare?

 

To further educate the industry about the benefits associated with CGP, Illumina, a California-based biotechnology company, established Access to Comprehensive Genomic Profiling (ACGP) in 2020, which is an alliance of seven members, including leading molecular diagnostics companies, pharmaceutical manufacturers, and laboratories. ACGP aims to educate about CGP for advanced cancer patients by engaging directly with the US payers.

Additionally, a few strategies are being adopted by the healthcare industry, such as bundling CGP tests with other diagnostic tests to reduce the overall cost per test. This way, instead of running a CGP test and a separate test for a specific genetic mutation, both tests could be combined into one-panel tests. This could reduce the overall cost per test by eliminating the need to run two separate tests, as well as reducing the need for multiple lab visits and samples. However, it’s important to note that the savings may vary depending on the specific tests and the laboratory.

The ambiguity surrounding reimbursement for CGP tests among the insurers also stems from the FDA’s ongoing debate over proper classification and regulatory framework for these tests. While the FDA recognizes the potential benefits of CGP, concerns linger about its quality, accuracy, and cost-effectiveness. To address these concerns, the FDA has been working with stakeholders to establish reimbursement policies that make CGP tests accessible to patients. These stakeholders range from academic institutions (such as Mayo Clinic and Memorial Sloan Kettering) to health insurance companies (such as UnitedHealthcare and Aetna) to CGP test developers (such as Guardant Health and Foundation Medicine).

Payers’ coverage for CGP is expanding but is highly uneven

Payers, such as Aetna and Cigna, have included CGP tests in their health plans but do not cover all types of cancers. While an increasing number of payers is expanding coverage for CGP, there is a lot of variation in terms of what is covered and for which types or stages of cancer.

For instance, Aetna announced in 2020 that it would cover CGP testing for certain types of breast and colorectal cancer. However, the coverage for each type of cancer gene mutation is different.

While Aetna’s policies for CGP coverage are very nuanced, Cigna’s are complicated. Cigna‘s coverage varies depending on the type of CGP test being ordered, whether the test is considered medically necessary for the patient’s condition, and the patient’s location. Sometimes, the patient needs to meet certain criteria to be eligible for coverage (e.g., only the advanced stage of cancer is considered under coverage).

Similarly, UHC, one of the leading private health plan providers in the USA, also limited its CGP coverage to patients with advanced cancers, such as lung, breast, or colorectal cancer. However, in early 2023, UHC issued a new policy expanding coverage for CGP tests from Foundation Medicine and Guardant Health. The new policy covers CGP tests for a wider range of cancers, including early-stage cancers and other types of tumors. The goal of this policy change is to increase access to CGP testing and to help catch cancer earlier when it is more treatable.

Aetna and Cigna are not far behind in expanding their coverage for CGP tests. In 2023, both companies included additional benefits for members receiving CGP testing, such as on-site care in some facilities and counseling services.

There’s an increasing recognition that CGP can help identify patients who may benefit from targeted therapies. Overall, payers are becoming more open to covering CGP, but there is still variability in their policies and coverage levels.

EOS Perspective

The adoption of CGP is creating a ripple effect throughout the healthcare industry. Payers are increasingly recognizing the value of CGP tests and expanding their coverage. By providing broader coverage for CGP tests, payers can position themselves as offering more cutting-edge care options. This can give them a competitive edge over other insurers who may not provide coverage for these tests. In addition, by broadening the coverage of tests for early-stage cancer, payers can help to identify and treat cancers earlier, which can lead to better outcomes for patients and potentially lower costs in the long run.

Further, the growing adoption of CGP has an impact on healthcare industry stakeholders beyond payers. It is likely to fuel a shift towards precision medicine, where treatments are tailored to the individual patient based on genetic information.

Diagnostic companies are likely to invest in CGP technology to stay competitive and offer more comprehensive tests. For healthcare providers, offering CGP tests allows them to differentiate themselves, improve patient outcomes, and attract more patients. However, it can also add complexity to the treatment process and increase costs if not managed correctly (e.g., wrong interpretation of genetic information due to the large amount of data for individual patients).

For test kit producers and labs, CGP is creating new opportunities for growth and market share but also increased competition and pressure to lower costs and improve accuracy.

Overall, while still not fully embraced by the industry, CGP is shaking up the healthcare landscape, creating both great opportunities and new challenges for all stakeholders.

Inflated COVID-19 Tests Prices in Africa Why and What Now by EOS Intelligence
by EOS Intelligence EOS Intelligence No Comments

Inflated COVID-19 Test Prices in Africa: Why and What Now?

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With the subsidence of COVID-19 and the announcement of the ending of the Global Health Emergency by WHO in May 2023, the world has started to move on and embark on its path back to pre-COVID normalcy. However, some of the lessons the pandemic has brought are hard to forget. One such lesson, and more importantly, an issue that demands attention and action, is the prevalent price disparity of COVID-19 tests in low-income regions of the world, such as Africa, compared to some more affluent countries, such as the USA.

High test prices across Africa, in comparison with prices in more developed parts of the world, such as the USA, have become evident after the onslaught of COVID-19 on the African continent. To illustrate this with an example, the average selling price of SD Biosensor’s STANDARD M nCoV Real-Time Detection kit comprising 96 tests per kit in the USA is US$576 compared to US$950 in African countries. This translates to a unit price of US$6 in the USA compared to US$9.9 in African countries, amounting to a 65% difference between the price points in the two regions. The price disparity in Africa vis-à-vis the USA ranges from +30% to over +60% in the case of PCR-based COVID-19 tests in our sample when compared to the prices of the same products that are being sold in the USA. This leads to the crucial question of why these tests are so costly in a place where they should be sold at a lower price, if not donated, owing to the continent’s less fortunate economic standing.

The Why: Reasons for inflated price in Africa

Several factors, such as Africa’s heavy dependence on medical goods imports, a limited number of source countries exporting medical goods to the continent, paucity of local pharma producers, higher bargaining power of foreign producers enabling them to set extortionate prices, shipping and storage costs, and bureaucratic factors drive the inflated prices of COVID-19 test kits in African countries.

Africa is heavily dependent on imports for its diagnostic, medicinal, and pharma products. To elucidate this, all African countries are net importers of pharma products. Additionally, the imports of medicines and medical goods, such as medical equipment, increased by around 19% average annual growth rate during the span of 20 years, from US$4.2 billion in 1998 to US$20 billion in 2018.

In 2019, medical goods accounted for 6.8% of total imports in Sub-Saharan Africa (SSA), whereas they accounted for only 1.1% of exports. The SSA region experiences a varied dependence on the imports of medical goods. This is evident from the fact that Togo and Liberia’s share of imports of medical goods was around 2%, while that of Burundi was about 18% in 2019.

The 2020 UNECA (United Nations Economic Commission of Africa) estimates suggest that around 94% of the continent’s pharma supplies are imported from outside of Africa, and the annual cost is around US$16 billion, with EU-27 accounting for around 51% of the imports, followed by India (19%), and Switzerland (8%). This means that only 6% of the medicinal and pharma products are produced locally in the African continent, creating a situation where foreign producers and suppliers have drastically higher bargaining power.

This became particularly evident during the 2020-2022 COVID-19 pandemic, when the demand for COVID-19 tests was extremely high compared to the supply of these tests, making it easier for foreign suppliers to set an exploitative price for their products in the African continent.

The lack of competition and differentiation in the region aggravated the situation further. There are only a handful of suppliers and producers in the continent that provide COVID-19 tests. To elucidate this further, there were only 375 pharmaceutical producers in the continent as of 2019 for a population of over 1.4 billion people. When compared with countries with similar populations, such as India and China, which have around 10,500 and 5,000 pharmaceutical companies, respectively, the scarcity in the African continent starts to manifest itself more conspicuously. To illustrate this further, only 37 countries in Africa were capable of producing medicines as of 2017, with only South Africa among these 37 nations able to produce active pharmaceutical ingredients (APIs) to some extent, whereas the rest of the countries had to depend on API imports.

Furthermore, the SSA region gets medical goods supplies from a small number of regions, such as the EU, China, India, the USA, and the UK. As of 2019, over 85% of the medical goods that were exported to SSA were sourced from these five regions. It is interesting to note that the source countries slightly differ for the SSA region and the African continent as a whole, with the EU and India being the common source regions for both. With a 36% share in all medical goods imports to the African continent in 2019, the EU is the top exporting region of medical goods to SSA, albeit with a declining share over the last few years. India and China share the second spot with a 17-18% share each in all medical goods imports supplied to SSA in 2019. Considerable concentration is observed in the import of COVID-19 test kits to SSA, with a 55% share in all medical goods imports supplied by the EU and a 10% share by the USA in 2019.

To provide a gist of how the above-mentioned factors attributed to the inflated prices of COVID-19 tests in the region, Africa’s medical goods industry, being import-driven, is heavily dependent on five regions that supply the majority of the medical goods needs of SSA. In addition to this, the scarcity of local pharma producers across the continent aggravated the situation further. This, in turn, gave an opportunity for foreign producers to charge a higher price for these COVID-19 tests in Africa.

Additionally, storage and shipping costs of COVID-19 tests also play a significant role in the pricing of these tests. The actual share of shipping and storage costs is difficult to gauge owing to the fact that there is not enough transparency in disclosing such pieces of information by test producers and suppliers.

Another aspect contributing to the inflated prices of these tests in African countries is bureaucratic factors. According to Folakunmi Pinheiro, a competition law writer based in Cambridge, UK, some African state governments (such as in Lagos) take exorbitantly high cuts on the sale of COVID-19 tests, allowing labs to keep no more than 19-20% of the profits per test after covering their overhead costs such as electricity, IT, logistics, internet, salary, and consumables costs including PPE, gloves, face masks, etc.

Since labs in Africa must purchase these tests from foreign producers, they have limited room for maneuvering with their profit margin, given the high test price and the cuts imposed by the local governments. Pinheiro further simplifies the profits in absolute terms. The cost of a PCR-based COVID-19 test, analyzed in laboratories (not at-home tests), in Lagos in February 2022 was around NGN45,250 (~US$57.38), and the labs selling and performing these tests on patients would make a profit of around NGN9000 (~US$11.41) per test which translates to 19.89% of the total cost of the single test. It is believed that this profit is after the overhead costs are covered, implying that the majority of the profits go to the state government of Lagos.

Inflated COVID-19 Tests Prices in Africa Why and What Now by EOS Intelligence

Inflated COVID-19 Tests Prices in Africa Why and What Now by EOS Intelligence

The What Now: Reactions

To combat the inflated prices of COVID-19 tests developed by foreign producers, many African price and competition regulatory organizations undertook efforts to reduce the prices of these tests to a significantly lower level in their respective countries. While R&D was ongoing for the making of groundbreaking low-priced alternative testing technologies that were ideal for African climate and economic conditions, many academic institutes tied up with foreign companies to launch these tests in the African markets. Additionally, the African Union (AU) and Africa CDC had set new goals to meet 60% of the vaccine needs of the continent domestically by fostering local production by 2040. Lastly, many African countries were able to eliminate or reduce import tariffs on medical goods during the pandemic for a considerable amount of time.

  • From price or competition regulatory bodies

As a response to the high PCR-based COVID-19 test prices in South Africa, the country’s Competition Commission (CCSA) was successful in reducing the prices for COVID-19 testing in three private laboratories, namely Pathcare, Ampath, and Lancet by around 41%, from R850 (~US$54.43) to R500 (~US$31.97) in January 2022. The CCSA asked these private clinical laboratory companies for financial statements and costs of COVID-19 testing as part of the investigation that started in October 2021. CCSA further insisted on removing the potential cost padding (an additional cost included in an estimated cost due to lack of sufficient information) and unrelated costs and thus arrived at the R500 (~US$31.97) price. Furthermore, the CCSA could significantly reduce the price of rapid antigen tests by around 57% from R350 (~US$18.96) to R150 (~US$8.12). However, it is believed that there was still room for further reduction in rapid antigen test price because the cost of rapid antigen tests in South Africa was around R50 (US$2.71). Although the magnitude to which this price reduction was possible is hard to analyze owing to the fact that there was not enough transparency in revealing the cost elements by these test producers.

  • From local producers, labs, and academia-corporate consortia

The fact that Africa is a low-income region with lower disposable income compared with affluent countries, in addition to its unfavorable climate, has driven local scientists to develop alternative, low-cost testing solutions with faster TAT and minimal storage needs.

African scientists were believed to have the potential to develop such cheaper COVID-19 tests, having had the necessary know-how gained through the development of tests for diseases such as Ebola and Marburg before. The high prices of COVID-19 tests in the African markets have compelled local universities to tie up with some foreign in-vitro diagnostic (IVD) producers to develop new, innovative, low-cost, alternative technologies.

To cite an example, the Senegal-based Pasteur Institute developed a US$1 finger-prick at-home antigen test for COVID-19 in partnership with Mologic, a UK-based biotech company. This test does not require laboratory analysis or electricity and produces results in around 10 minutes. This test was launched in Senegal as per a December 2022 publication in the Journal of Global Health. Although this test’s accuracy cannot match the high-throughput tests developed by foreign producers, the low-cost COVID-19 tests proved to be useful in African conditions where large-scale testing was the need of the hour and high-temperature climate was not conducive to cold storage of other types of tests.

Countries such as Nigeria, Senegal, and Uganda tried to increase their testing capacity with their homegrown low-cost alternatives as the prices of the tests developed by foreign manufacturers were exorbitantly high. Senegal and Uganda stepped up to produce their own rapid tests, while in remote areas of Nigeria, field labs with home-grown tests were set up to address the need for COVID testing that remained unaddressed because of the high prices of the foreign tests.

Dr. Misaki Wayengera, the pioneer behind the revolutionary, low-cost paper strip test for rapid detection of filoviruses including Ebola and Marburg with a TAT of five minutes, believes that a low-cost, easy-to-use, point-of-care (POC) diagnostic test for detecting COVID-19 is ideal for equatorial settings in Africa providing test results within a shorter time span while the patient waits. He spearheaded the development of a low-cost COVID-19 testing kit with a TAT of one to two minutes, along with other Ugandan researchers and scientists.

  • From the African Union and CDC Africa

As an aftermath of the adversities caused by the COVID-19 pandemic, the African Union (AU) and African Centers for Disease Control and Prevention (CDC Africa) put forth a goal of producing 60% of Africa’s vaccine needs locally by 2040. A US$ 45 million worth of investment was approved in June 2023 for the development of vaccines in Africa under the partnership of Dakar, Senegal-based Pasteur Institute (IPD), and Mastercard Foundation. The goal of MADIBA (Manufacturing in Africa for Disease Immunization and Building Autonomy) includes improving biomanufacturing in the continent by training a dedicated staff for MADIBA and other vaccine producers from Africa, partnering with African universities, and fostering science education amongst students in Africa.

Additionally, the US International Development Finance Corporation (DFC), in partnership with the World Bank Group, Germany, and France, announced in June 2021 a joint investment to scale up vaccine production capacity in Africa. The investment was expected to empower an undisclosed South African vaccine producer to ramp up production of the Johnson & Johnson vaccine to over 500 million doses (planned by the end of 2022).

  • From FTAs such as the Africa Continental Free Trade Agreement

Intra-regional trade within Africa (as opposed to overseas trade) from 2015 to 2017 was only 15.2% of total trade, compared to 67% within Europe, 61% within Asia, and 47% within the Americas. While supply chain disruptions hampered the availability of COVID-19 testing kits, many African nations could develop home-grown solutions locally to address the issue. Africa Continental Free Trade Agreement (AfCFTA) was set up on January 1, 2021, with the intention of improving intra-regional trade of goods, including medical supplies. AfCFTA, the largest FTA after WTO, impacts 55 countries constituting a 1.3 billion population in an economy of US$3.4 trillion. Inadequate intercontinental collaboration is one of the primary restraints for medical supply chains. In order for health systems to fully capitalize on AfCFTA, partnerships with the African Union’s (AU) five Regional Collaborating Centers and current global healthcare organizations need to be increased.

  • From state governments

Sub-Saharan African countries have the highest MFN (most favored nation) tariff rate (9.2%) on medical goods, compared to developed nations’ tariffs (1.9%) as well as emerging economies’ tariffs (6.6%). However, out of 45 countries in Sub-Saharan Africa, only eight countries could remove or decrease import tariffs and value-added taxes on medical goods on a temporary basis to aid the public health situation during the pandemic in 2020, as per Global Trade Alert. These eight countries include Angola, Chad, Malawi, Mauritius, Niger, Nigeria, South Africa, and Zambia. In three of these eight countries, these measures had already expired as of April 2021. Furthermore, to promote intra-regional trade, 33 Sub-Saharan African countries provide preferential tariff rates of around 0.2% on average on some medical products. At the same time, the average MFN tariff rate for the same medical goods is around 15% for these Sub-Saharan African countries.

EOS Perspective

Since the demand for COVID-19 test kits was significantly higher compared to their supply, producers and suppliers had a higher bargaining power, because of which they set an extortionate price. However, that being said, African competition authorities did their best to curb the prices, although there was still room for more.

Secondly, policy changes need to be brought about at the state level to allow increased competition in the African markets, which in turn would lower the price of the tests. African governments need to consider a more patient-centric and consumer-protective approach wherein competition is likely to facilitate the launch and consequent market uptake of better-quality products available at lower prices.

Additionally, prices and costs of COVID-19 tests should be monitored on a regular basis. The underlying problem of inflated COVID-19 test prices is likely to cease only when competition in the PCR testing sector is encouraged, and government policies of pricing the tests are more patient-oriented.

Moreover, robust intra-regional trade coupled with strong local manufacturing and lower trade barriers is expected to help build Africa’s more sustainable health system.

by EOS Intelligence EOS Intelligence No Comments

Powering Healthcare Diagnostics with AI: a Pipe Dream or Reality

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The growing paucity of radiologists across the globe is alarming. The availability of radiologists is extremely disproportionate globally. To illustrate this, Massachusetts General Hospital in Boston, USA, had 126 radiologists, while the entire country of Liberia had two radiologists, and 14 countries in the African continent did not have a single radiologist, as of 2015. This leads to a crucial question – how to address this global unmet demand for radiologists and diagnostic professionals?

Increasing capital investment signals rising interest in AI in healthcare diagnostics

The global market for Artificial Intelligence (AI) in healthcare diagnostics is forecast to grow at a CAGR of 8.3%, from US$513.3 million in 2019 to US$825.9 million in 2025, according to Frost & Sullivan’s report from 2021. This growth in the healthcare diagnostics AI market is attributed to the increased demand for diagnostic tests due to the rising prevalence of novel diseases and fast-track approvals from regulatory authorities to use AI-powered technologies for preliminary diagnosis.

Imaging Diagnostics, also known as Medical Imaging is one of the key areas of healthcare diagnostics that is most interesting in exploring AI implementation. From 2013 to 2018, over 70 firms in the imaging diagnostics AI sector secured equity funding spanning 119 investment deals and have progressed towards commercial beginnings, thanks to quick approvals from respective regulatory bodies.

Between 2015 and 2021, US$3.5 billion was secured by AI-enabled imaging diagnostics firms (specialized in developing AI-powered solutions) globally for 290 investment deals, as per Signify Research. More than 200 firms (specialized in developing AI-powered solutions) globally were building AI-based solutions for imaging diagnostics, between 2015 and 2021.

The value of global investments in imaging diagnostics AI in 2020 was approximately 8.8% of the global investments in healthcare AI. The corresponding figure in 2019 was 10.2%. The sector is seeing considerable investment at a global level, with Asia-based firms (specialized in developing AI-powered solutions) having secured around US$1.5 billion, Americas-based companies raising US$1.2 billion, and EMEA-based firms securing over US$600 million between 2015 and 2021.

As per a survey conducted by the American College of Radiology in 2020 involving 1,427 US-based radiologists, 30% of respondents said that they used AI in some form in their clinical practice. This might seem like a meager adoption rate of AI amongst US radiologists. However, considering that five years earlier, there were hardly any radiologists in the USA using AI in their clinical practice, the figure illustrates a considerable surge in AI adoption here.

However, the adoption of AI in healthcare diagnostics is faced with several challenges such as high implementation costs, lack of high-quality diagnostic data, data privacy issues, patient safety, cybersecurity concerns, fear of job replacement, and trust issues. The question that remains is whether these challenges are considerable enough to hinder the widespread implementation of AI in healthcare diagnostics.

Powering Healthcare Diagnostics with AIPowering Healthcare Diagnostics with AI

AI advantages help answer the needs in healthcare diagnostics

Several advantages such as improved correctness in disease detection and diagnosis, reduced scope of medical and diagnosis errors, improved access to diagnosis in areas where radiologists are unavailable, and increased workflow and efficacy drive the surge in the demand for AI-powered solutions in healthcare diagnostics.

One of the biggest benefits of AI in healthcare diagnostics is improved correctness in disease detection and diagnosis. According to a 2017 study conducted by two radiologists from the Thomas Jefferson University Hospital, AI could detect lesions caused by tuberculosis in chest X-rays with an accuracy rate of 96%. Beth Israel Deaconess Medical Center in Boston, Massachusetts uses AI to scan images and detect blood diseases with a 95% accuracy rate. There are numerous similar pieces of evidence supporting the AI’s ability to offer improved levels of correctness in disease detection and diagnosis.

A major benefit offered by AI in healthcare diagnostics is the reduced scope of medical and diagnosis errors. Medical and diagnosis errors are among the top 10 causes of death globally, according to WHO. Taking this into consideration, minimizing medical errors with the help of AI is one of the most promising benefits of diagnostics AI. AI is capable of cutting medical and diagnosis errors by 30% to 40% (trimming down the treatment costs by 50%), according to Frost & Sullivan’s report from 2016. With the implementation of AI, diagnostic errors can be reduced by 50% in the next five years starting from 2021, according to Suchi Saria, Founder and CEO, Bayesian Health and Director, Machine Learning and Healthcare Lab, Johns Hopkins University.

Another benefit that has been noticed is improved access to diagnosis in areas where there is a shortage of radiologists and other diagnostic professionals. The paucity of radiologists is a global trend. To cite a few examples, there is one radiologist for: 31,707 people in Mexico (2017), 14,634 people in Japan (2012), 130,000 people in India (2014), 6,827 people in the USA (2021), 15,665 people in the UK (2020).

AI has the ability to modify the way radiologists operate. It could change their active approach toward diagnosis to a proactive approach. To elucidate this, instead of just examining the particular condition for which the patient requested medical intervention, AI is likely to enable radiologists to find other conditions that remain undiagnosed or even conditions the patient is unaware of. In a post-COVID-19 era, AI is likely to reduce the backlogs in low-emergency situations. Thus, the technology can help bridge the gap created due to radiologist shortage and improve the access to diagnosis of patients to a drastic extent.

Further, AI helps in improving the workflow and efficacy of healthcare diagnostic processes. On average at any point in time, more than 300,000 medical images are waiting to be read by a radiologist in the UK for more than 30 days. The use of AI will enable radiologists to focus on identifying dangerous conditions rather than spend more time verifying non-disease conditions. Thus, the use of AI will help minimize such delays in anomaly detection in medical images and improve workflow and efficacy levels. To illustrate this, an AI algorithm named CheXNeXt, developed in a Stanford University study in 2018 could read chest X-rays for 14 distinct pathologies. Not only could the algorithm achieve the same level of precision as the radiologists, but it could also read the images in less than two minutes while the radiologists could read them in an average of four hours.

Black-box AI: A source of challenges to AI implementation in healthcare diagnostics

The black-box nature of AI means that with most AI-powered tools, only the input and output are visible but the innards between them are not visible or knowable. The root cause of many challenges for AI implementation in healthcare diagnostics is AI’s innate character of the black box.

One of the primary impediments is tracking and evaluating the decision-making process of the AI system in case of a negative result or outcome of AI algorithms. That is to say, it is not possible to detect the fundamental cause of the negative outcome within the AI system because of the black-box nature of AI. Therefore, it becomes difficult to avoid such occurrences of negative outcomes in the future.

The second encumbrance caused by the black-box nature of AI is the trust issues of clinicians that are hesitant to use AI applications because they do not completely comprehend the technology. Patients are also expected to not have faith in the AI tools because they are less forgiving of machine errors as opposed to human errors.

Further, several financial, technological, and psychological challenges while implementing AI in healthcare diagnostics are also associated with the black-box nature of the technology.

Financial challenges

High implementation costs

According to a 2020 survey conducted by Definitive Healthcare, a leading player in healthcare commercial intelligence, cost continues to be the most prominent encumbrance in AI implementation in diagnostics. Approximately 55% of the respondents who do not use AI pointed out that cost is the biggest challenge in AI implementation.

The cost of a bespoke AI system can be between US$20,000 to US$1 million, as per Analytics Insights, while the cost of the minimum viable product (a product with sufficient features to lure early adopters and verify a product idea ahead of time in the product development cycle) can be between US$8,000 and US$15,000. Other factors that also decide the total cost of AI are the costs of hiring and training skilled labor. The cost of data scientists and engineers ranges from US$550 to US$1,100 per day depending on their skills and experience levels, while the cost of a software engineer (to develop applications, dashboards, etc.) ranges between US$600 and US$1,500 per day.

It can be gauged from these figures that the total cost of AI implementation is high enough for the stakeholders to ponder upon the decision of whether to adopt the technology, especially if they are not fully aware of the benefits it might bring and if they are working with ongoing budget constraints, not infrequent in healthcare institutions.

Technological challenges

Overall paucity of availability of high-quality diagnostic data

High-quality diagnostic and medical datasets are a prerequisite for the testing of AI models. Because of the highly disintegrated nature of medical and diagnostic data, it becomes extremely difficult for data scientists to procure the data for testing AI algorithms. To put it in simple terms, patient records and diagnostic images are fragmented across myriad electronic health records (EHRs) and software platforms which makes it hard for the AI developer to use the data.

Data privacy concerns

AI developers must be open about the quality of the data used and any limitations of the software being employed, without risking cybersecurity and without breaching intellectual property concerns. Large-scale implementation of AI will lead to higher vulnerability of the existing cloud or on-premise infrastructure to both physical and cyber attacks leading to security breaches of critical healthcare diagnostic information. Targets in this space such as diagnostic tools and medical devices can be compromised by malware or software viruses. Compromised data and algorithms will result in errors in diagnosis and consequently inaccurate recommendations of treatment thereby causing stakeholders to refrain from using AI in healthcare diagnostics.

Patient safety

One of the foremost challenges for AI in healthcare diagnostics is patient safety. To achieve better patient safety, developers of AI algorithms must ensure the credibility, rationality, and transparency of the underlying datasets. Patient safety depends on the performance of AI which in turn depends on the quality of the training data. The better the quality of the data, the better will be the performance of the AI algorithms resulting in higher patient safety.

Mental and psychological challenges

Fear of job substitution

A survey published in March 2021 by European Radiology, the official journal of the European Society of Radiology, involving 1,041 respondents (83% of them were based in European countries) found that 38% of residents and radiologists are worried about their jobs being cut by AI. However, 48% of the respondents were more enterprising and unbiased towards AI. The fear of substitution could be attributed to the fact that those having restricted knowledge of AI are not completely educated about its shortcomings and consider their skillset to be less up-to-date than the technology. Because of this lack of awareness, they fail to realize that radiologists are instrumental in developing, testing, and implementing AI into clinical practice.

Trust issues

Trusting AI systems is crucial for the profitable implementation of AI into diagnostic practice. It is of foremost importance that the patient is made aware of the data processing and open dialogues must be encouraged to foster trust. Openness or transparency that forges confidence and reliability among patients and clinicians is instrumental in the success of AI in clinical practice.

EOS Perspective

With trust in AI amongst clinicians and patients, its adoption in healthcare diagnostics can be achieved at a more rapid pace. Lack of it breeds fear of job replacement by the technology amongst clinicians. Further, scarcity of awareness of AI’s true potential as well as its limitations also threatens diagnostic professionals from getting replaced by the technology. Therefore, to fully understand the capabilities of AI in healthcare diagnostics, clinicians and patients must learn about and trust the technology.

With the multitude and variety of challenges for AI implementation in healthcare diagnostics, its importance in technology becomes all the more critical. The benefits of AI are likely to accelerate the pace of adoption and thereby realize the true potential of AI in terms of saving clinicians’ time by streamlining how they operate, improving diagnosis, minimizing errors, maximizing efficacy, reducing redundancies, and delivering reliable diagnostic results. To power healthcare diagnostics with AI, it is important to view AI as an opportunity rather than a threat. This in turn will set AI in diagnostics on its path from pipe dream to reality.

by EOS Intelligence EOS Intelligence No Comments

Diagnostics Gain Spotlight amid Coronavirus Outbreak

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It took 60 days for global COVID-19 infections to reach 100,000, but this figure doubled in the following 12-14 days, and the addition of next 100,000 cases took only 3 more days. Because of highly contagious nature of the novel coronavirus, testing became essential to keep the epidemic under control. As a result, there was a spike in global demand for coronavirus testing kits. As per McKinsey’s estimates, in May 2020, global demand for coronavirus testing was 14 million to 16 million per week, but less than 10 million tests were being conducted.

Industry was quick to respond to the rise in demand

The widespread outbreak of coronavirus required the manufacturers to develop and launch new testing kits in large volumes in a short duration of time. Diagnostics kit suppliers responded promptly to this spike in demand by developing new coronavirus testing kits. Roche Diagnostics, for instance, developed coronavirus test in about six weeks – such diagnostic tests generally take 18 months or more to reach regulatory review stage. In 2020, Roche developed a total of 15 solutions for coronavirus diagnosis.

Governments across the world eased up regulatory procedures for manufacturers in order to allow rapid development and commercialization of the coronavirus testing kits. This paved way for many companies to quickly launch new products to the market. For instance, a Korean firm, Seegene, developed coronavirus testing kit in two weeks and got approval from Korea Centers for Disease Control and Prevention (KCDC) in another two weeks’ time. Such approvals generally take more than six months in Korea.

Furthermore, standard regulatory process for approval of diagnostic kits in the USA typically take several months, but considering the public health emergency in the event of pandemic, the FDA issued emergency use authorizations to expedite the process of bringing coronavirus test kits to the market. Emergency use authorizations are like interim approvals provided on the basis of sufficient evidence to suggest a diagnostics test is effective and the benefits outweighs potential risks.

By the end of 2020, the FDA granted emergency use authorization to 225 diagnostic tests for coronavirus detection, including test kits developed by Abbott Laboratories, Roche, Cepheid, Clinomics, Princeton BioMeditech, UPenn, Inno Diagnostics, Ipsum Diagnostics, Co-Diagnostics, QIAGEN, DiaSorin, BioMérieux, and Humanigen.

Leading companies with adequate resources quickly ramped up their production capacity by multifold in line with the rising demand. For instance, a US-based firm, Thermo Fisher Scientific, increased the global production of coronavirus test kits from 50,000 per week in January 2020 to 10 million per week by June 2020. In 2020, Roche spent CHF 137 million (~US$149 million) to ramp up production capacity and supply chain for all COVID-19-related testing products.

Some companies also received government grants and private investment to scale up their production capacity. For instance, in July 2020, BD (Becton, Dickinson and Company) received a US$24 million investment from the US government to scale up production of coronavirus test kits by 50%, thereby, enabling the company to produce 12 million test kits per month by the end of February 2021.

The pandemic encouraged the shift towards decentralizing diagnostics

While the test kit manufacturers were trying to achieve round the clock production to meet the demand, they struggled with global supply chain disruptions which were also induced by the pandemic.

Coronavirus testing requires several components including specialized chemicals and laboratory testing equipment. Roche, for example, manufactures coronavirus tests in the USA but procures components of the test kit from different countries. One of the important components of test kits is reagent, a specialized liquid used for the identification of coronavirus. Roche produces these reagents mainly in Germany and few other production sites located across the world.

Further, the test kits are often compatible only with company’s own testing equipment and systems. For instance, the Roche cobas SARS-CoV-2 test kit runs on the cobas 6800 or 8800 systems. The cobas 8800 system includes approximately 23,000 components which are procured from different parts of the world. In addition to this, the production involves 101 sub-assemblies and accumulated assembly time of about 450 hours each. Final production of these instruments from Roche takes place in Switzerland.

Manufacturing of a coronavirus testing kit involves complex supply chain. Spread of coronavirus forced countries to implement extreme measures including lockdowns and trade restrictions which impacted the supply chain of test kit manufacturers. Producing all the testing components and equipment at one place is near to impossible. For instance, the production of reagents involves highly sophisticated and sensitive processes, and thus, setting up a new production site to manufacture reagents on a large scale would take several months. Setting up a new production site and streamlining the procurement for such testing equipment and systems would take several years. Hence, the diagnostics firms upped their R&D activities in an effort to develop tests that could be conducted without sophisticated laboratory systems and equipment.

Moreover, the high demand for testing compelled the diagnostics practices to evolve far beyond the traditional laboratory-based business model. The need for community testing during the pandemic that challenged the operational capabilities of hospitals and diagnostics labs dictated the importance of decentralizing diagnostics for improved patient care. This gave rise to increased demand for point-of-care testing.

The two most widely used diagnostic tests for coronavirus detection are Reverse Transcription Polymerase Chain Reaction (RT-PCR) and Antigen tests. RT-PCR test detect viral RNA in samples from the upper and lower respiratory tract, while antigen test is used to detect viral proteins in samples.

RT-PCR test is considered gold standard for coronavirus detection since the accuracy and reliability is high compared to Antigen test. However, RT-PCR test needs to be processed in a laboratory-setting and had turnaround time of several hours. Hence, there was a need for development of RT-PCR tests that could give faster results without the support of laboratory equipment.

On March 18, 2020, Abbott announced the launch of their first coronavirus test kit that was compatible with their system ‘m2000 RealTime’ which processed 470 tests in 24 hours and another ‘Alinity m’ system with capacity to run 1,080 tests in a 24-hour period. Since there was demand for more portable and fast testing solution, on March 30, 2020, Abbott launched a RT-PCR point-of-care test that ran on ID NOW system, which is the size of a small toaster. The test delivers results in 13 minutes or less. The test price is in the range of ~US$100.

Further, despite the limitations of accuracy and reliability, in some cases antigen test is preferred because there is no requirement of a lab specialist to conduct this test, thus making it less expensive, and the result is available in a few minutes. The industry saw an opportunity here and quickly developed rapid antigen tests that can be conducted at home without any assistance. For instance, in December 2020, the US FDA granted emergency use authorization to an Australia-based firm Ellume’s antigen test (priced at ~US$30) as first over-the-counter at-home diagnostic test for coronavirus detection. Soon after, Abbott also received emergency use authorization from FDA for its at-home rapid antigen test (priced at US$25) giving results in 15 minutes.

Other countries around the world also followed the suit by extending official authorization to the home-based tests for coronavirus detection. For instance, in February 2021, Germany’s Federal Institute for Drugs and Medical Devices (BfArM) granted special approval for the first time to antigen home-test kits developed by US-based Healgen Scientific as well as China-based firms Xiamen Boson Biotech and Hangzhou Laihe Biotech.

Diagnostics Gain Spotlight amidst Coronavirus Outbreak by EOS Intelligence

Coronavirus crisis accelerated innovation in the field of diagnostics

In a united fight against the pandemic, governments, private sector, as well as NGOs and philanthropists across the world stepped forward to raise funds to bolster R&D efforts in coronavirus diagnostics. As per data compiled by Policy Cures Research (an Australian firm engaged in global health R&D data collection and analysis), from January 2020 to September 2020, funds worth over US$800 million were committed for coronavirus diagnostics R&D. The firm also indicated that 450+ coronavirus diagnostics products were in R&D pipeline since January 2020 to December 2020.

With firms looking to capitalize on exponentially rising demand for coronavirus testing, the development of new diagnostics technologies beyond conventionally used tests (i.e., RT-PCR and antigen tests) picked up significantly.

For instance, in May 2020, the FDA granted an emergency use authorization to first ever CRISPR-based rapid test kit developed by Sherlock Biosciences. CRISPR, an acronym for Clustered Regularly Interspaced Short Palindromic Repeats, is a gene editing technology which allows to alter the DNA. Sherlock’s rapid test is a paper-strip test (like a pregnancy test) which can be conducted at point-of-care and does not require any additional equipment for processing of the test. The test works by programming a CRISPR enzyme to release a detectable signal in presence of genetic signature for coronavirus.

In March 2020, US-based Surgisphere launched a smartphone app using Artificial Intelligence algorithms to detect coronavirus infection. This app confirms diagnosis by integrating the findings of chest CT scan and laboratory tests with clinical symptoms and exposure history. Preliminary studies found that the tool can detect coronavirus infection with 95.5% accuracy.

Further, application of nanotechnology for diagnosis of coronavirus infection is also underway. Canada-based Sona Nanotech developed a rapid antigen test using gold nanoparticles. This is a strip test that can be conducted at point-of-care and gives result in 15 minutes. Research is in progress to develop wearable sensors using nanoparticles for detection of coronavirus. In January 2021, University of California San Diego received US$1.3 million from the National Institutes of Health to develop a test strip containing nanoparticle that change color in presence of coronavirus. This test strip can be attached on a mask and used to detect coronavirus in a user’s breath or saliva.

Innovation wave was not limited to development of different types of tests but also expanded to consumables. For instance, in March 2020, HP (a company manufacturing 3D printers) teamed up with Beth Israel Deaconess Medical Center (a teaching hospital of Harvard Medical School) to develop 3D printed nasopharyngeal swab (typically used to collect sample for coronavirus testing) and within 35 days the clinically validated swab was ready for use. By May 2020, these swabs were commercially available for the US market following the FDA approval. In June 2020, a Belgium-based 3D printing service provider, ZiggZagg, began to plan large-scale production of swabs on their fleet of HP 3D printers. By October 2020, the company had 3D-printed over 700,000 swabs for the Belgian market.

EOS Perspective

A market research firm, The Business Research Company, estimated that the global COVID-19 rapid test kits market was expected to reach a value of US$14.94 billion in 2020. Due to worldwide vaccination drive, the market is expected to decline at a rate of -54.9%, to reach US$1.37 billion in 2023.

Though the demand for coronavirus tests is expected to diminish eventually, it has supported rapid development of diagnostics infrastructure which will remain. In India, for example, only one laboratory was performing molecular assays for COVID-19 in January 2020. The COVID-19 pandemic has shifted that balance. By May 2020, some 600 Indian RT-PCR laboratories had been set up in an effort to help manage the pandemic, thousand-fold increasing testing capacity. The additional capacity will likely remain in place as the pandemic subsides, leaving the RT-PCR assay as the dominant method for diagnosing most viral infections in India in the future.

Furthermore, with surge in demand for the coronavirus testing, the provision of diagnostic services expanded beyond the purview of hospitals and laboratories. Mobile testing facilities and drive-through testing sites propped up with development of point-of-care diagnostics. For instance, Walgreens, one of the largest pharmacy chains in the USA, offer coronavirus drive-thru testing at 6,000+ locations across the country. Further, there is high-demand for home-based testing.

Diagnostics firms riding high on the COVID-19 gains have been actively scouting opportunities to strengthen their positioning in the market and prepare for the post-pandemic world. High demand for COVID-19 test kits boosted the revenues of diagnostic companies, with Roche, Thermo Fisher, PerkinElmer, Hologic, and DiaSorin among the companies benefiting. With strong balance sheet, these companies went on with M&A flurry to advance their diagnostic portfolio and other core business verticals.

As the virus originated in China, the country was better prepared and first to develop relevant detection mechanisms. By the time the virus spread to the other parts of the world, Chinese companies were ready to export detection kits globally. Coronavirus outbreak helped China to penetrate major markets such as EU and the USA in which the indigenous diagnostics companies traditionally had a stronger hold. China was a net importer of diagnostic reagents and test kits in 2019. But in 2020, after the outbreak of coronavirus, China ramped up its production capacity of diagnostic reagents and test kits, and as a result its export growth increased by more than 500% and the country became a net exporter of diagnostic reagents and test kits by the end of 2020.

This indicates that the outbreak of the pandemic has shifted the market dynamics on many fronts. As the pandemic slowly subsides, some of these shifts might partially revert, however, the way testing is performed is likely to remain.

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