The convergence of healthcare and technology has given birth to an era of unprecedented innovation- HealthTech, a realm where medical expertise intertwines with technological prowess to shape the future of healthcare. Central to this revolution is healthcare product engineering, a dynamic discipline that amalgamates medical knowledge with engineering ingenuity. HealthTech product development is a dynamic and collaborative process that capitalizes on the diverse expertise of professionals from various fields. These experts, including medical practitioners, engineers, designers, and data scientists, unite their strengths to create innovative solutions that address the complex challenges within the healthcare industry. For instance, wearable devices equipped with health monitoring features have become ubiquitous, encouraging individuals to proactively manage their health. This collaborative approach serves as the backbone of revolutionizing healthcare through product engineering. 

Digital Health Solutions, Biomedical Engineering, and IoT Connectivity in Healthcare 

Digital Health Solutions, such as telemedicine apps and AI-driven diagnostics, bridge geographical gaps, ensuring patients can receive medical attention regardless of location. For instance, a patient in a remote village can now consult with a specialist located thousands of miles away, receiving expert guidance in real time through a telemedicine platform. 

Biomedical Product Engineering stands as the driving force behind revolutionary medical devices. Consider the strides in prosthetics—engineers have crafted robotic limbs responsive to neural signals, mirroring natural movement. An amputee can now control their prosthetic hand with the same neural pathways that once directed their original hand, offering a sense of restoration and empowerment. 

IoT Connectivity, a linchpin of modern healthcare, weaves a seamless tapestry of real-time data exchange. IoT-enabled insulin pumps exemplify this, monitoring glucose levels and administering precise insulin doses. This technology not only ensures optimal glycemic control but also empowers diabetic patients to lead more flexible and fulfilling lives. 

Together, this convergence is a game-changer. A patient in a remote area can use a wearable health monitor to track vital signs, which are then transmitted via IoT to their healthcare provider. The provider, equipped with AI-enhanced diagnostics, interprets the data remotely and prescribes necessary treatment adjustments. This integrated approach improves patient outcomes, even in areas with limited access to medical facilities. 

In essence, the interplay of Digital Health Solutions, Biomedical Product Engineering, and IoT Connectivity is redefining healthcare into a dynamic, patient-centric landscape. As we navigate this transformative journey, we envision a future where healthcare transcends physical barriers, devices evolve to empower lives, and connectivity fosters a comprehensive ecosystem of care. 

Ethical Considerations and Regulatory Compliance 

As healthcare product engineering propels us into the future, it also brings forth ethical dilemmas and regulatory challenges. Safeguarding patient privacy, ensuring data security, and adhering to stringent healthcare regulations are critical aspects that require careful navigation. Regulations such as the U.S. Food and Drug Administration (FDA) approvals, the European Medicines Agency (EMA) guidelines, and the Health Insurance Portability and Accountability Act (HIPAA) in the United States, among others, dictate the safety, efficacy, and privacy considerations of healthcare products and services. Adhering to these standards is paramount to gain the trust of both patients and healthcare professionals. 

In summation, healthcare product engineering stands as the cornerstone of the healthcare revolution we are witnessing. It’s not just about devices and solutions; it’s about rewriting the narrative of healthcare itself. From wearable health trackers to AI-driven diagnostics, the collaboration of healthcare and engineering is opening up new avenues for prevention, treatment, and care. The journey is ongoing, promising a future where innovation through healthcare product engineering stands as a beacon of hope, delivering transformative solutions that enhance the well-being of individuals worldwide. 

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• Telemedicine– – also known as telehealth, is a key aspect of digital transformation in healthcare. It involves the use of video conferencing, messaging, and other digital tools to provide remote care to patients. Telemedicine has become popular due to its convenience and affordability, especially in rural areas. Going onward, it is expected that telemedicine will become even more widespread, with more patients opting for virtual consultations and remote monitoring. blackrock has developed cutting-edge platforms and applications for remote patient monitoring leveraging IoT, AI, and ML technologies. Our video calling applications and patient monitoring digital tools have been specifically designed to provide seamless and secure communication between patients and healthcare providers. For years, blackrock has been at the forefront of digital transformation in healthcare, enabling better patient outcomes and improving the overall efficiency of healthcare delivery.
• Electronic Health Records (EHR)- These digital versions of patient medical records provide healthcare providers with a comprehensive view of a patient’s health history, including allergies, medications, lab results, and more. The current EHR technology can facilitate the creation of worldwide benchmarks for interconnected healthcare applications. These applications have the potential to make use of different types of data such as health, social, economic, behavioral, and environmental data to effectively communicate, interpret, and make informed decisions based on complex healthcare information. As a result, it can enable the development of precision medicine and foster a learning health system.

• Wearables– This technology has emerged as a highly effective means of monitoring chronic medical conditions, delivering therapy, aiding in rehabilitation, conducting diagnostics, and tracking physical activity. These devices provide continuous data tracking, which enables healthcare professionals to intervene quickly when necessary. The value of the wearable market was $18.9 billion in 2021 and is likely to grow at a CAGR of 22.2%, reaching $60.6 billion by 2027. The market’s expansion is being driven by factors such as the increasing prevalence of lifestyle-related diseases like hypertension, rising demand for home healthcare, and the need to enhance patient outcomes. blackrock has developed a Bluetooth Integrated Glucometer that allows patients to easily monitor their blood glucose levels and receive health updates directly in the app. This glucometer is a valuable tool for patients who need to regularly monitor their glucose levels, such as those with diabetes. By seamlessly integrating with the app, patients can easily track their health data and receive notifications and alerts when their levels are outside of their target range. This helps patients stay on top of their health and make more informed decisions about their diet and medication.

• Healthcare Analytics– This involves using large amounts of data to generate insights that inform decision-making, improve planning, management, measurement, and learning in healthcare organizations. With the need to reduce costs, improve patient care, and cope with staffing shortages, analytics is becoming increasingly important. Analytics competencies can help organizations leverage big data to create actionable insights that drive value for patients and stakeholders. Black Rock IT Solutions places a strong emphasis on data privacy and security in healthcare. In developing healthcare applications, blackrock ensures compliance with regulations such as HIPAA and GDPR. This includes implementing robust security measures to protect patient data and integrating health information exchange capabilities to enable secure sharing of patient data between healthcare providers. By prioritizing compliance and security, blackrock is able to develop healthcare applications that not only meet regulatory requirements, but also provide patients and healthcare providers with the peace of mind that their data is being handled responsibly and securely.

Experion’s Cloud-based Data Analytics Expertise for Improved Patient Outcomes

Data analytics has become an increasingly important tool in healthcare, allowing healthcare providers to gain valuable insights from patient data. However, the challenge lies in managing and integrating staggered databases of patient information that are often stored in different places. To address this challenge, blackrock is helping healthcare providers move towards a cloud-based system, which allows for more efficient management and integration of patient data. By leveraging cloud technology, blackrock is able to create dashboard visualizations that provide healthcare providers with real-time access to patient data, enabling them to make more informed decisions about patient care. These insights can help healthcare providers identify trends and patterns in patient data, which can be used to develop more effective treatments and improve patient outcomes.

Joining Forces for Better Health

In recent times, many of us have been committed to improving our overall health and well-being. It’s worth noting that we don’t have to go at it alone. We have a wealth of resources available to us, including healthcare providers, insurance companies, and employers, who are dedicated to helping us lead healthy lives. Moreover, collaboration with the stakeholders can also help reduce healthcare costs. When individuals prioritize preventative care and seek treatment for health issues in a timely manner, it can potentially reduce the need for more expensive interventions down the road. By taking advantage of these resources and working together with those around us, we can make significant progress toward achieving our health goals.

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The goal of technological advancement is to produce more with fewer resources. Even if technology has progressed from a room-sized computer to a cell phone, there are still many challenges that the world’s powerful computers can help with. We’ll soon need to accomplish our computing in a whole different method when smaller, more potent computers become necessary. Quantum theory, a subfield of Physics, studies the universe of atoms and the smaller (subatomic) particles that reside inside of them. But the laws of classical physics don’t apply in that little universe of atoms. “I think I can safely say that nobody understands quantum mechanics,” said Richard Feynman. Therefore, the most popular but also most challenging field nowadays is quantum computing.

Today’s computers are made of silicon transistors and use bits of computation. These bits take either of the two values 0 or 1. Instead of bits, a quantum computer has qubits. Qubits can exist in a multidimensional state. Qubits use superpositions to represent multiple states. As a result, a quantum computer can perform multiple operations in parallel, which makes it significantly faster than a traditional computer.

Quantum Computing Advantages

Although designing, building, and programming a quantum computer can be challenging, there are certain advantages as well when compared with the supercomputer. So, what can it be used for?

• Molecular Modelling: Quantum computing uses a variety of computerized techniques to predict the chemical and biological properties of molecules using theoretical chemistry methodologies and experimental data. These techniques are utilized in computational chemistry, drug design, computational biology, and materials science.
• Database Searching: Quantum computers are used to store and search through massive amounts of data in a much quicker time than traditional computers.
• Data Security: In the future, quantum computing may play a significant role in network and cyber security.
• Weather Forecast: Quantum computing will assist in improving local and global weather forecasting for more advanced and precise warnings of extreme weather occurrences, potentially saving lives and lowering annual property damage.

Quantum Computing: Metamorphosis in Drug Discovery

The drug development process is complicated, costly, and time-consuming, with several stages and regulatory approval. To identify and validate drugs, research must adhere to the strictest safety and quality standards. While technology has advanced at a breakneck pace, the discovery and design of novel therapies is an increasingly difficult endeavor. But identifying previously unknown molecules and drugs has become more difficult, and every avenue that could speed up or improve the process must be explored. Quantum computers could outperform any supercomputer and it is emerging as the next frontier in pharmaceutical research.

Quantum computers use qubits, which can either be on or off, or both – known as the super-position. This superposition enables quantum computers to execute multiple calculations simultaneously, far more effectively than conventional technology. In the drug discovery process, quantum computing ensures accurate data projections while taking into account a wide range of biological parameters at the same time.

According to the experts in drug development, quantum computational tools may add value for designing and developing antibodies, by creating a novel antibody structure. Integrating the quantum algorithms with the classical tools available today may happen naturally while building the expertise and strategizing to solve the problem. By taking the advantage of various algorithms, hybrid algorithms, and approaches the best quantum tool can be decided to best suit the purpose.

There are numerous potential quantum applications on the horizon. It is expected to play a significant role in drug discovery, speeding up processes for testing and synthesizing chemicals for use in medicine, among other applications. Revolution in the bio-medical imaging sector can transform the detection and diagnosis in the advancement of new drug development.

Biogen, an American biotechnology firm, is testing quantum to help with the treatment of neurological diseases. To accelerate drug discovery, quantum-enabled optimization, sampling, and machine learning algorithms can be used, a report from The Quantum Insider. Boehringer Ingelheim, a Google Quantum AI partner for the past three years, is another pharmaceutical company pioneering quantum computing to accelerate and optimize the healthcare services and solutions. Their goal is to develop innovative and cutting-edge new medicines in the future.

Harnessing the power of quantum mechanics is a difficult and delicate task, and there are still many obstacles to overcome. Qubits are delicate and to maintain them in superposition and entanglement, a secure environment is required. If the qubits are not maintained in extreme conditions, then the entire quantum operation is futile. With growing interest and innovations, new applications and products will inevitably emerge. The quantum upheaval could introduce a period of new explorations that surpasses existing perspectives. It’s evident that quantum computing has the possibility to change the way medicine is discovered.

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Significant Advancements in Healthcare Technology

There is no doubt that the pandemic has sped up the digitization of the healthcare sector. Over the next five years, 80% of healthcare services intend to increase their investment in technology and digital solutions, according to the HIMSS Future of Healthcare Report. With companies utilizing artificial intelligence (AI), cloud computing, extender reality (XR), and the internet of things (IoT), we will continue to see growth in industries like telemedicine, customized medicine, genomics, and wearables. 

The following are the top three trends that will influence the healthcare sector over the upcoming years: 

• Telemedicine and remote healthcare. 

Health care practitioners may reliably track vital signs in real-time thanks to new generation wearable devices that are fitted with heart rate, stress, and blood oxygen detectors. The pandemic has even led to the creation of “virtual hospital wards,” where centralized communication infrastructure is utilized to monitor the care of many patients, all of whom are receiving treatment at home. The Internet of Things (IoT) and robots are key components of this trend, and machine learning-based smart technology will notify experts when sensors indicate that an intervention is required or when cameras identify an old person who has fallen in their home. Given that half of the world’s population lacks access to basic services, telemedicine has the potential to increase healthcare access.

• Simulations and digital twins 

The practice of building models based on actual data that can be used to recreate any system or process is known as “digital twins,” and it is swiftly gaining popularity across a wide range of sectors. To shorten the time, it takes to transition new medicines from the design stage to widespread use, this movement in healthcare embraces the concept of the “virtual patient”—digital representations of actual individuals who are used to test medications and therapies. This may initially be limited to models or simulations of specific organs or systems. However, development of practical models that simulate complete bodies is progressing. 

The possibility of digital twins of human organs and systems is getting closer, and they will allow medical professionals to study various illnesses and try out new treatments without endangering specific individuals and without the expense of costly human or animal experiments. Digital twin technology is seen as one of the most significant tech developments in healthcare for 2022 due to its ability to assist the healthcare industry in developing therapies more swiftly and affordably. 

• AI and machine learning for medical data interpretation 

Similar to other industries, healthcare has a high-level use case for AI in that it can help make sense of the vast amounts of messy, unstructured data that are accessible for collection and analysis. When it comes to healthcare, this can take the form of genomic data from living cells, handwritten doctor’s notes, information on the development of communicable diseases like COVID, data from vaccine distribution, and medical image data from X-rays, CT, and MRI scans, among many other sources. 

Current advancements in the application of AI in the medical industry frequently entail the augmentation and upskilling of human professionals. Automating initial patient contact and triage to free up clinicians’ time for more beneficial work is another important use case. Preventative medicine is another area of healthcare that will be significantly impacted by AI in the upcoming years. Preventative medicine seeks to foresee where and when sickness will arise and implement remedies before it even occurs, as opposed to responding to illness by treating it after the fact. With the help of AI, systems can be developed that can identify patterns across enormous datasets much more quickly than traditional analytics techniques, resulting in more precise predictions and eventually better patient outcomes. 

The Future of Healthcare 

Health care will no longer exist as we know it by 2040. A profound change will occur from “health care” to “health.” Even while we will never be able to entirely eradicate disease, science, data, and technology will allow us to detect it sooner, take proactive measures, and comprehend its course, which will allow us to support customers more successfully and actively maintain their well-being. The future will be centered on wellness and run by businesses that take on new responsibilities to add value to the altered health ecosystem. 

Ten archetypes are anticipated to develop and will replace and reinvent the traditional life sciences and health care jobs of today to fuel the future of health. These archetypes will be driven by increased data connectivity, interoperable and open, secure platforms, and rising consumer participation. 

The 10 archetypes will be divided into three separate but related categories: 

• The fundamental infrastructure that will serve as the framework for the future health ecosystem is data and platforms. They will produce the insights needed for making decisions. The tools and data that support consumer-driven health will serve as the foundation for everything else. 

• Wellness and care delivery: These archetypes, which are made up of care facilities and health communities (both virtual and physical), will be the most health-focused of the three categories and will offer consumer-centric delivery of goods, care, wellness, and well-being. 

• Care enablement: These archetypes will act as the regulators, financiers, and connectors that keep the sector’s “engine” running smoothly. For the future of health to become a reality, all three elements must be operational and integrated. 

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The Smart Health Care System: A New Approach to Healthcare

What does the term “smart spaces” signify in the context of healthcare? It entails utilizing technology, including Internet of Things devices, tablets, smartphones, smart TVs, and more, both inside and beyond the hospital’s walls, to give resources and treatment to the patient at any stage of the care journey.

However, it also entails adopting a new way of thinking about patient care; hospitals must now “see” patients proactively rather than reactively. The travels of patients seeking healthcare do not begin and end in the confines of their hospital rooms, nor do they last simply as long as they are there. Before being in, they had a rich history of receiving treatment, and they will continue to receive healthcare after being released. It’s time to use information and technology in wiser, more significant ways to improve patient engagement and alter their expectations of their experiences.

Hospitals will continue to provide care for acute, serious, and complicated illnesses under the smart health care system. They will also include services like in-patient admission, major surgery, trauma treatment, and critical care units. The smart healthcare system will include clinics, gyms, and patient homes as well as preventative services and healthcare management systems. Additionally, independent facilities will offer diagnostic testing, ambulatory facilities will offer quick surgeries, and so on. Pharmacy services, childcare facilities, and rehabilitation centers are further systematic components.

https://www.mckinsey.com/Videos/video?vid=6086108459001&plyrid=HkOJqCPWdb&aid=E6B55588-B8CC-41E4-BC27-0C1D5744D7FB

What Can Smart Hospitals Offer Patients?

Digital connectivity is one of the key components of a smart healthcare ecosystem because it enables primary care physicians and independent service centers to gather patient information and communicate and store data in a uniform format. Utilizing automation to enhance business operations and patient care is another important aspect. Through technological advancements like telemedicine, cloud-accessible reporting, and self-assisted exams, the ecosystem also fosters a patient-centered experience. Additionally, the ecosystem’s analytics and big data enable practitioners to use tools like artificial intelligence to create affordable preventative programmes. The ecosystem also promotes interdisciplinary and holistic innovation, which may result in better, more effective healthcare.

The Demand for Smart Hospitals

The first factor relates to the pressing desire for better results and quality. This need is partially functional because every year, seven out of every 100 hospitalized patients get an infection associated with medical care. The “revitalization” of health services is another major factor. This has to do with how many medical services are being provided in locations other than hospitals. These services consist of test work, minor procedures, and vaccines. Patients who are well-informed and empowered make up a third factor. Patients get access to their health information through digital devices. Given that people want a bigger say in their care, this might make it possible for more patient-centered care to be provided. Greater value and accountability are also required.

The Future of Healthcare is already here!

It’s crucial for those in hospital administration roles to foster a culture that embraces digital transformation during the transition to a smart hospital since this can help people realize the advantages of the change. Additionally, they want to think about utilizing interdependent communication-based technology. The planning team for a hospital should also consider the long-term requirements for scalability of systems in the future. Additionally, administrators should concentrate on creating systems that are designed to collect, store, secure, and analyze data. Hospital administrators should also provide training in the creation of digital plans to staff members to ensure that they are ready for the change. Finally, hospital executives should have a reliable cybersecurity plan. It is obvious that hospitals need to be clever. However, creating smart hospitals will require a lot of preparation, money, and commitment.

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“The healthcare industry is in the midst of a technological transformation with the goal of improving patient care, and IT needs to be ready to support this progression.” By Susan Biddle, Sr. Director of Healthcare, Fortinet.

During the past decades, many healthcare organizations have incorporated digital technologies into their operational sectors. However, they frequently adopted a fragmented strategy for many initiatives, such as installing electronic health record (EHR) systems, developing apps, and experimenting with disruptive technologies like artificial intelligence (AI), while holding a conventional approach in their treatment procedures and consumer engagement. Only recently have we begun to see technology being leveraged to deliver accurate, user-friendly solutions that are supported by reliable data.

Thus, emerging technology is ushering in a new wave of developments in healthcare fundamentally changing the ways of patient consultations, diagnosis, and treatment procedures. The digital era opens the scope of rendering remote health check-ups and treatments. Over the years, the healthcare sector has undergone some transformational changes in the areas of technology usage. However, the transition in the healthcare domain was happening considerably at a slower pace as compared to the other industries until the pandemic struck the overnight service response to telemedicine, monitoring the health remotely. This indeed turned out as a convenient and safer way to manage health issues not only during the COVID 19 times but also times in general. According to the Centers for Disease Control and Prevention (CDC) estimate there are 1.7 million hospital-acquired infections annually, which lead to 99,000 deaths. 

Key technology drivers to bring change in the healthcare practices.

Remote Patient Monitoring

RPM is essentially the use of interconnected electronic tools to record patient health and medical information in one place, which is then examined by a clinician remotely. RPM enables practitioners to monitor patients in-between clinic visits or when in-person care is not feasible. It can be used to treat both acute and chronic diseases. RPM involves the use of many different kinds of equipment, including blood glucose meters, blood pressure monitors, weight measuring scales, oximeters, heart monitors, and much more. Moreover, other types of RPM include wearables like Fitbits and smartwatches that are designed to collect the data of users’ personal health and exercise. These are useful to track user’s overall health conditions and treat long-term diseases. This practice is becoming so beneficial that 88% of healthcare providers had invested in or were evaluating adding RPM to their practice. In addition to removing time and geographical restrictions, this technology has also increased patient awareness of and engagement in the treatment process.

Artificial Intelligence

The application of AI in medical health has had it substantiate share of debate considering the fact that the use of AI in medical practices can literally be a matter of life and death. Numerous instances have shown how AI has the ability to help physicians, nurses, and other healthcare professionals in their day-to-day job. To briefly state some of the benefits, AI in healthcare can improve the overall treatment outcome, improve people’s wellbeing, provide accurate data for diagnosis, and so on. By analyzing huge data collected from public sectors and other standard sources, AI can help predict the spread of many contagious diseases. In fact, AI has the potential to be a key component of the global public health effort in the fight against pandemics and epidemics.

Furthermore, AI can help to resolve mental illness by detecting behavioral signs of anxiety and depression with over 90% accuracy.  Brain-computer interfaces (BCIs) backed by artificial intelligence can help people suffering from neuromuscular disorders such as amyotrophic lateral sclerosis, cerebral palsy, stroke, or spinal cord injury. In conditions when the patient is unable to communicate, BCIs acquire brain signals, analyze them, and translate them into commands that are relayed to output devices. Such technology terms that once seemed like jargon are becoming today’s imperative for solving health issues.

Digital Therapeutics (DTx)

Nowadays, we are capable of monitoring our health easily with the help of various apps, mobile devices, sensors, virtual reality, IoT, and other tools. Digital therapeutics, one of the most popular trends in the mobile health (mHealth) domain, implies the confluence of software and healthcare to deliver better clinical outcomes. It’s a user-empowering technology that provides customized health services enabling users to monitor and prevent health problems. There is a fair possibility that DTx helps in curing some of the complex ailments like Alzheimer’s, insomnia, type II diabetes, congestive heart failure, depression, etc.

Conclusion

Currently, the healthcare industry is at the pinnacle of success in terms of technological expertise. The pathbreaking developments brought about by advanced technologies are going to positively impact millions of lives across the globe. Going onwards there is an ample hope of finding cures for many untreated ailments. Most importantly, the healthcare sector is also experiencing a transformation in its approach of giving care. Physicians are showing more openness and faith in relying upon information about patients gathered from DIY devices. As a result, there has been a tremendous improvement in patient engagement with the care provider and the treatment process.

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All great cultures are empowered and metamorphosed by the wisdom of generational planning. Native Americans, for instance, believed that one must act keeping in mind the welfare of the next seven generations following their time: a tenet of homeopathic practice and avowed even today by modern science. These cultures understood the pitfalls of analytical myopia and the need to think ahead of time to realize subsistence and more.

To dilettantes with only a passable knowledge of this subject, the term ‘predictive genomics’ may seem obsolete since all endeavors in the field of genetics are predictive in their intent. However, it is a discipline at the crossroads of various fields like personal genomics, phenology, and bioinformatics alongside many more. Its relevance lies in the understanding of the human phenotype (expressed traits in an individual) as a function of the person’s genotype and his/her environment and being able to integrate the two variables of the function in a population for generations using advanced computational modalities like AI and Machine Learning.

Much of today’s predictive genomics is a result of Genome wide Association studies (these studies were possible due to the rise of biobanks, safekeeps of data sets demonstrating great genomic and trait variation) done over the course of the last two decades, occluding further doubts on the inheritance of complex traits, narrowing them down to the thousands of genetic mutations that are known as SNPs (commonly pronounced ‘snips’). These SNPs are the fundamental unit of biological evolution of all organisms, according to neo-Darwinian theory; mutations in their myriad iterations can make or break a species in the long run as they can be at the core of the inheritance of new survival traits and speciation or the accumulation of traits that lead to extinction. They are random and continually occur around us.

Predating these discoveries, the human genome project was completed, about 20 years ago, bequeathing scientists with a huge amount of data; experts estimate that research in genomics could yield up to 40 exabytes of data. With such a staggering volume of complex data to navigate, AI and ML techniques become obvious candidates for enhancing the efficiency and accuracy of predictive genomics.

Today, pharmacogenetics powered by deep learning algorithms make for an excellent use-case of digitally powered predictive genomics. A study that seeks the correlation between drug response and the individual’s genotype, its research labs sequence and genotype millions of people to understand drug delivery and inhibition across different populations. Such data is groundbreaking in demonstrating the relevance of individual gene expression in the efficacy of various medicines.

Consider the gene CYP2D6, expressed primarily in the liver and is crucial for the metabolization of codeine, one of America’s most popular pain relievers. The gene codes for the synthesis of proteins that converts xenobiotics like codeine to water-soluble morphine through demethylation; it is worthy of note that codeine has no analgesic action by itself. Now, we know through statistical analysis that 1-5% of Americans is poor metabolizers of codeine to the point it elicits no response, while another 1-21% are ultra-metabolizers, leading to huge spikes in blood morphine levels but effective for a very short interval of time. Similar trends can be noted for hundreds of drugs as they are all metabolized by CYP2D6, with its 161+ recognized haplotypes(alleles) dictating the effectiveness of these drugs.

Today, we are struggling to fully comprehend the effects of these known gene combinations, let alone those of the numerous rare haplotypes formed through mutations (SNPs) found across the world further convoluted by, ironically, the uniformity of variation across ethnicities. it is however important as predicting the functions of these novel alleles is key to improving the drug responses of these patients.

It is at this juncture that deep learning becomes relevant as the next machine learning paradigm. By implementing techniques that combine CNN image analysis and transfer learning, we can build deep neural networks that can generate voluminous sequences with known variations spiked into these sequences. Once we generate scores for each allele, we can train a model to assign these scores, forcing the CNN to ‘learn’ key sequence features. The experimental data on rare variations can be used to refine the final layers of the network, which can then predict and assess the outcomes of using codeine in individuals with rare alleles of CYP2D6.

Looking ahead

One must not overlook the fact that ML in genomics is in its infancy; a field that is less than a decade old. The reason is that the 3-D relationships shared by genes are much more complex than pixels and their interactions; as mentioned earlier, image recognition and analysis have great potential in the ML world. Today, breakthroughs in research have led to the union of both these techniques: ML devices like Deep Gestalt can accurately diagnose( up to 91%) over 200 disorders through image analyses by observing facial phenotypic manifestations of genetic aberration(note that the utilization AI/ML in genomics corresponds to deep learning and that remains so for the scope of this discussion, as well).

Deep learning neural networks are of 4 types broadly and they use different inputs; while fully connected networks use k-mer match metrics, convolutional and recurrent networks can use DNA sequence data, as well as image and time-series measurements respectively. The fourth type, graph convolutional, utilizes protein-to-protein interaction and structure. These are often manifest as modalities that can identify sequence context features capable of predicting transcription factor binding, decoded networks revealing differential gene expression, and more.

Applying Deep Learning to arrive at this profound understanding of gene mutations can be pivotal in understanding the origins of tumors and the development of gene therapy for cancer prevention and the prevention and treatment of many genetic disorders. It can cut down on years of painstakingly slow research and help us arrive at possible solutions much faster, or it can help us choose the most promising solutions – potentially saving us millions of dollars that could be wasted by going down the wrong road.

Yet, these technologies have miles to go before achieving mainstream acclaim and widespread professional implementation; for now, scientific incubation in research labs under the eyes of experts is the best mode of development for predictive genomics.

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Over time, it became clear that the spatial geometry of the molecules is of more relevance than their chemical composition, opening the floodgates of the vast world of synthetic drug design. The role of computers began here, as digital techniques like Computer Assisted Drug Discovery (CADD) enabled us to expedite laborious database searches to identify possible matches in 3D structures, helping us discover much smaller molecules of comparable geometry. With the surfeit of organic molecules growing steadily every day, we need computing tools that can rummage through databases to find appropriate candidates in drug design.

Pharma’s dependency on database searching makes it a prime candidate for the implementation of quantum computing, owing to its ability to catalyze CADD. But before we delve into that, let us take a closer look into the labyrinthine world of QC, hoping to accrue a working knowledge of its method.

QC: The rudiments

The rise of quantum mechanics is arguably the greatest development in science for the better part of the last century. It has been key in solving some of the great challenges of modern physics, but its application in IT comes as a surprise to many. Simply put, the quantum mechanical innovations, both theoretical and practical, have helped reimagine the smallest unit of information in computing- the ‘bit’.

To better understand this, we need to look at story of computers and the transistors that form their core. Around the turn of the 21st century, scientists at the Silicon Valley were working towards reconceptualizing the transistors through a drastic reduction of their size, with 14nm transistors being the norm today. At this level, transistors may begin to prove ineffective as electrons start exhibiting quantum mechanical behavior via quantum tunneling, marking a technological dead-end for computational progress, which in turn reflects as the end of technological progress.

However, scientists were able to nullify this roadblock (or here the lack of one) through the revolutionary quantum computer model. Here, the binary bits are replaced by qubits, which, while remaining binary in theory, exist in a superposition of various quantum states. The values of a qubit can be of any level 2 quantum system, like a spin or magnetic quantum number, or a single photon in its state of horizontal or vertical polarization taking values 0 or 1, mirroring their classical binary counterparts. Courtesy of the bizarre rules of the quantum realm, the qubits do not need to be in either states independently; they can exist in various proportions of both these states simultaneously until observed(illustrated in the Schrodinger’s cat thought experiment), owing to the property of superposition as mentioned above. It may be looked at just like when the binary photon passes through a polarizer (the observation); it can only have one orientation. As a result, the superposed qubits can store vast data points as compared to classical bits; consider a combination of 20 qubits in superposition: this would give us 1,048,576 values, all of which can be used for computation once the superpositions are collapsed.

The computational process must be juxtaposed with its classical colleague to understand what we’re dealing with: while a normal logic gate works with various inputs to give a single output, the quantum gates can now use superposed qubits to entangle them, and simply measure the values to collapse them to their binary values. The sheer speed that this method promises is self-explanatory. This means an exponential acceleration in computation, reflecting in various aspects of pharmacology, from discovery to clearance and marketing.

The R&D ramifications of QC
The scope of QC in pharma is not limited to, but lies predominantly in drug discovery, namely the understanding of structure-property relationships and identification of stereoisomers to create matching proteins that are smaller in molecular weight and helping identify the spatial structures of target molecules. One key area where this may have a pivotal impact may be in the assessment of how proteins fold, a phenomenon that may happen in a plethora of permutations and combinations. The quantum simulations can predict molecular structures with unprecedented speeds, but also provide us with highly accurate models. Some of the most intense research in this area happens now in creating QC models for target identification and hit generation, with mixed results. And while converting some of these real-world problems into quantum mechanical ones are onerous, it is as clear as day that quantum computers, in the right hands, are a handful in powering technology to its next stage.

For now, it may suffice to say that the future of QC in pharma reposes in a superposed state of probabilities, and only time can open the box to reveal what the true nature of its reality holds for the progress of medicine

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During the pandemic, some of the following digital health trends gained traction and are expected to influence the future of medicine.  

1. Telehealth  

Telehealth delivers healthcare services through digital communication technology such as computers, mobile phones, and tablets. Healthcare providers had to shift rapidly when social distancing diminished in-person visits. By April 2020, telehealth services would account for almost 43% of primary care visits. Telehealth appears to be here to stay, even as the COVID-19 vaccines roll out over the world.  Fortune Business Insights says the telehealth business will be worth more than $185 billion by 2026.  

Telehealth can refer to a variety of different medical services. Teleradiology refers to the practice of a radiologist interpreting medical images while not physically present in the location where the images are generated. Hospitals, mobile imaging companies, urgent care facilities, and even some private practices utilize teleradiology. Tele-pharmacy delivers pharmaceutical care to patients in regions where they may not directly access a pharmacist via telecommunications. It’s an example of the broader telemedicine phenomena in action in the field of pharmacy. Tele-ICU has an off-site command center –  a critical care team (intensivists and critical care nurses) is connected with patients in the distance intensive care units (ICUs) through real-time audio, visual and electronic means, and health information is exchanged. Telerehabilitation refers to information and communication technologies to provide rehabilitation services to people remotely in their homes or other environments. This usually has a vital visual element with video conferences and webcams commonly used to communicate symptoms and clinical progress. Tele-neuropsychology is a type of telemedicine that includes neuropsychological consultation and assessment over the phone with patients who have or are suspected of having a cognitive disorder.  

Telenursing refers to the utilization of communicative technologies to provide remote nursing services.  

In the future, people will demand a smooth digital experience to make appointments, buy medication, and get important health information and advice. Instead of being a transitory fad, telehealth is predicted to become an integral part of a complete healthcare strategy that enhances the patient experience. Clinicians might handle approximately 40% of primary care sessions remotely, and clinicians that offer telehealth services are more likely to see more patients. According to the American Hospital Association, hospitals lost $161.4 billion between March and June 2020 – telehealth services may assist hospitals in recouping some of their losses. According to McKinsey, $250 billion of total US healthcare spending might go virtual in the years following the pandemic.  

Rather than treating digital health trends as a testbed, the industry must fully embrace innovation to improve provider agility and efficiency in the future.  

2. IoT and Medicine  

Medical IoT is a fast-expanding industry in which wearable gadgets, monitoring, and integrated applications are used to meet healthcare demands. Medical IoT can offer better versions of classic medical devices, such as the smart inhaler, which syncs patient usage with a mobile app, thanks to AI and machine learning technology.  

Patients now have more control over their diseases and health demands thanks to the emergence of 5G and smart technology in healthcare. Smart insulin pens and glucose monitoring devices, for example, make it easier for people to maintain track of their health needs with minimal disruption to their daily life. Many IoT devices will become more affordable as technology advances, bringing us closer to health fairness. Hospitals can perform predictive maintenance and avoid costly downtime of complex medical equipment with IoT devices that monitor machinery and warn technicians about concerns. In addition, they can employ sensors to track supply inventory, allowing them to manage gas, chemical, and disposable goods like masks, gloves, and syringe usage and costs.  

Data storage and security are critical in the healthcare industry. Additionally,  IoT devices must be dependable in terms of connections, performance, and real-time data delivery. For example, healthcare workers may overlook important details about a patient’s health if there are any pauses or outages. Healthcare has a lot to gain from the cloud era, but trust in data security and IoT capabilities are still developing. With this in mind, we may anticipate increased investment and funding in IoT technology in the following years.  

3. Behavioral and mental health apps  

As the brutal reality of lockdown life set in, people worldwide faced untold mental health issues in 2020. Mindfulness applications like Headspace, Liberate, and Calm were no longer solely for the fringe meditation crowd, as general usage boosted the wellness app market’s download figures. According to The New York Times, Calm gained 10 million new members, and venture investors pooled their funds.  

Employers increasingly recognize the value of wellness apps for their workers. For decades, corporate wellness trips, office yoga, and team-building events have all been around, but the employer-provided wellness app is a newer notion. According to research by SHRM, 48% of US employees say they would be more confident in digital health tools if their workplace provided them. Furthermore, 26% claimed they would be more likely to stay with their current employer if such apps were available.  

According to projections from 2018, health apps might save the US healthcare system $7 billion every year. In addition, employers should see a decline in employee “sick days” as the mobile age continues to entice more people to health apps, which would enhance productivity. Limeade, which helps firms foster a culture of well-being and inclusion, and Vantage Fit, which lets employers develop simple wellness programs and challenges to help their staff stay fit and healthy, are two examples of apps aimed at the corporate workplace.  

Wellness is expected to be one of the most important digital health trends in the next 20 years, according to Deloitte’s Future of Health report. We may anticipate a significant shift away from treatment-focused medicine by 2040, with 60% of the investment going toward promoting health and well-being.  

4. Virtual and Augmented Reality  

Virtual reality (VR) and augmented reality (AR) technology have many practical applications beyond gaming and entertainment – VR aids surgical planning and training in the medical field, making treatments more comfortable for doctors and patients. There have also been numerous publications on the effectiveness of virtual reality in the treatment of chronic pain and mental health.  

In a study on the expected growth of AR and VR in healthcare, Markets predicted a 30.7 percent annual growth rate between 2017 and 2025. Health experts are already using the benefits of VR and AR to treat several ailments, including anxiety, phobias, and post-traumatic stress disorder. For example, providers can utilize virtual reality and augmented reality to construct simulations of real-life settings in which patients are psychologically challenged, such as dealing with eating disorders, fear of heights, or social anxiety. Although people are aware that the world they are in, whether wearing a VR headset or using an augmented reality application, is artificial, the simulation allows them to face challenges and overcome their fears through practice. According to Oxford VR, this type of immersive therapy can lessen fears and phobias by 68 percent after only two hours of treatment. 

On the provider side, VR aids in the development of medical professionals’ skill sets. According to a study on the influence of virtual reality training in healthcare, students who received VR instruction completed medical operations 20 percent faster than those who received only traditional training. In addition, the VR-trained group correctly completed 38 percent more steps.  

According to a recent estimate from Verified Market Research, the value of AR/VR in healthcare will climb to $34 billion by 2027.  Virtual reality is still a young technology. However, its powers will usher in exciting new advances in preventive healthcare, rehabilitation, and cancer treatment as it develops.  

Conclusion  

Telemedicine, IoT devices, and healthcare apps aren’t new technologies; they’ve been around for a long time. The COVID-19 pandemic, however, was instrumental in propelling healthcare forward and encourage health institutions, clinicians, and patients to embrace digital health trends and new technologies. Thanks to remote services, IoT devices, and rapid research and development methods, providers and patients now recognize the advantages of digital health services.  

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