3D pill printer finishing one precisely formulated polypill to replace all other pills you take in a day.

The Vision of Tomorrow’s Medicine

Back in 2012, I wrote about the idea of 3D pill printers, envisioning a future where medications could be customized to each individual and printed on demand. At the time, it felt like an inevitable leap for healthcare—a logical extension of 3D printing’s growing capabilities and the burgeoning field of personalized medicine. In that column, I predicted that by now, we would have entered an era of precision medicine, where constant monitoring of our bodies and adaptive, on-demand medications would be the norm. What I didn’t realize was just how long it would take for this vision to begin materializing and how many barriers—technological, regulatory, and societal—would stand in the way.

Fast-forward to today, and while we’ve made significant strides, the dream of a 3D-printed polypill tailored to our exact needs remains tantalizingly just out of reach. Imagine waking up, glancing at your health dashboard, and receiving a notification that your personalized medication—customized for your body’s real-time condition—is ready to print. It’s a world where your treatment adapts as you do, responding to spikes in stress, changes in inflammation, or shifts in glucose levels. This isn’t science fiction; it’s a vision grounded in technologies already being developed, from wearable health trackers to AI-driven diagnostics and advanced drug manufacturing techniques.

But as we inch closer to this revolution, we must grapple with three important questions:

• How much further do we have to go?
• What challenges remain, and
• How will they shape the future of healthcare?

Precision medicine has the potential to transform lives, but only if we can navigate the complexities of building a system that is both innovative and equitable. It’s time to revisit that 2012 vision with a fresh perspective, informed by over a decade of progress, and consider how we can bring the promise of 3D-printed precision medicine to life.

24/7 health monitor that talks to your pill printer.

The Building Blocks of a Precision Medicine Revolution

1. Continuous Monitoring

At the heart of this transformation lies the ability to continuously monitor a patient’s health, an area that has already seen significant breakthroughs. Advances in wearable technology have paved the way for devices like smartwatches and fitness trackers that measure everything from heart rate variability to blood oxygen levels. These devices are becoming more sophisticated by the day, integrating sensors that can analyze blood glucose, hormone fluctuations, or even sweat composition without the need for invasive procedures. For patients with chronic conditions like diabetes or hypertension, implantable sensors take this a step further, offering round-the-clock monitoring with unparalleled accuracy.

The magic happens when this constant flow of data Is paired with artificial Intelligence. AI algorithms analyze these metrics in real-time, detecting subtle trends or anomalies that a human doctor might miss. For example, a sudden spike in inflammation markers could trigger an automatic adjustment in medication dosage, preventing complications before they escalate. This seamless integration of continuous monitoring and AI is not just about detecting illness; it’s about creating a proactive healthcare system that stays one step ahead of disease.

2. Polypills and 3D Printing

Complementing these monitoring systems is the emergence of polypills—a revolutionary concept in drug delivery. Polypills combine multiple medications into a single tablet, simplifying complex regimens and reducing the burden on patients managing multiple prescriptions. With 3D printing technology, the potential of polypills expands dramatically. Instead of mass-produced, one-size-fits-all formulations, 3D-printed polypills can be customized down to the molecular level. A single tablet can include precise doses of several drugs, and each layered for targeted release at different times throughout the day.

Beyond simplification, 3D printing also allows for the integration of supplements, like probiotics or vitamins, into the same pill. For patients with unique conditions or rare diseases, 3D printing offers a solution to the age-old problem of limited drug availability. These printers, connected to cloud-based systems, can synthesize the exact medication needed on-demand, and deliver it directly to the patient’s home.

3. AI and the Internet of Things (IoT)

Underpinning this revolution is the growing ecosystem of interconnected devices known as the Internet of Things (IoT). In this ecosystem, wearables, sensors, and 3D printers communicate seamlessly, creating a feedback loop between the patient, healthcare providers, and even digital health twins. These digital twins are virtual replicas of patients, capable of simulating physiological responses to various treatments. Before a polypill is printed, its effects can be tested on the digital twin to ensure safety and efficacy.

This interconnected network represents more than just convenience; it embodies a shift toward a truly patient-centric healthcare system. By connecting the dots between real-time monitoring, AI analytics, and on-demand drug manufacturing, the IoT is poised to transform not just how we treat illness but how we define wellness itself.

By only printing one pill a day means no bottles of pills laying around.

The Benefits of 24/7 Precision Medicine

The most striking promise of 24/7 precision medicine lies in its hyper-personalization. Traditional medications are often prescribed based on broad population averages, leaving significant room for error or inefficacy when applied to individuals with unique biological needs. Precision medicine, powered by real-time monitoring, takes an entirely different approach. By leveraging constant data streams from wearable sensors and AI-driven analytics, medications can be tailored to each individual’s exact condition and genetic makeup. Imagine a polypill dynamically adapting to fluctuations in a patient’s stress levels, inflammation markers, or blood sugar levels—an adaptive treatment designed to evolve with the patient’s ever-changing health metrics.

This level of personalization inevitably leads to improved patient outcomes. With drugs finely tuned to an individual’s needs, the likelihood of adverse side effects decreases dramatically. Gone are the days of trial-and-error prescribing, where patients endure unnecessary side effects or ineffective treatments. Additionally, the simplification of complex regimens into a single polypill ensures enhanced adherence. No more juggling multiple prescriptions or struggling to remember which pill to take and when. For patients managing chronic conditions, this can be life-changing, reducing both physical and emotional burdens.

Perhaps the most transformative aspect of 24/7 precision medicine is its potential to empower preventive care. Early detection becomes the new standard, as wearable devices and implantable sensors flag subtle changes in biomarkers long before symptoms appear. Conditions like heart disease, diabetes, or even cancer can be identified and managed in their earliest stages, drastically improving survival rates and reducing healthcare costs. Beyond just treating diseases, precision medicine integrates behavioral nudges to promote healthier lifestyles. Notifications reminding patients to hydrate, take a short walk, or prioritize sleep are rooted in real-time data, helping individuals make proactive choices to maintain their well-being. This holistic approach marks a fundamental shift from reactive to proactive care, with the patient at the center of a continuously evolving ecosystem of health optimization.

Finding the optimal level of privacy for 3D printing polypills will be difficult.

The Challenges on the Road to Reality

While the potential of 24/7 precision medicine is staggering, the path to realizing it is fraught with data privacy and ethical concerns. At the heart of this new healthcare paradigm lies an unprecedented volume of personal health data—sensitive information collected from wearables, sensors, and interconnected devices. This raises a critical question: who owns this data? If it falls into the wrong hands, the consequences could be dire, ranging from targeted hacking to the misuse of personal health information by insurers or employers. Ethical dilemmas abound, such as whether insurers should have the right to adjust premiums based on real-time health metrics or whether employers can mandate participation in continuous monitoring programs.

Regulatory and legal hurdles further complicate the adoption of precision medicine. The idea of dynamic, on-demand prescriptions is groundbreaking, but it presents a logistical nightmare for regulators tasked with ensuring patient safety. Every dose printed by a 3D printer must meet rigorous safety and efficacy standards, but how can this be guaranteed when treatments are being adjusted in real-time? The FDA and other regulatory bodies will need to rethink traditional approval processes, balancing innovation with oversight.

Even the technology itself poses significant challenges. The compatibility of multiple drugs within a single polypill remains a delicate issue, as some compounds may interact in ways that compromise their stability or effectiveness. Furthermore, creating universal standards for 3D printers and ensuring a consistent supply chain for the raw materials needed to manufacture custom medications is no small feat. Without these standards, the scalability of 3D-printed medications will remain limited.

Finally, there’s the issue of cost and accessibility. Precision medicine and 3D printing technology are likely to be expensive in their early stages, potentially limiting access to those who can afford it. This raises the specter of deepening healthcare inequality, where the wealthy benefit from cutting-edge advancements while marginalized populations are left behind. If precision medicine is to fulfill its promise, policymakers and innovators must address this imbalance, ensuring that its benefits are distributed equitably across all demographics.

The Dark Side of Always-On Medicine

The dream of always-on medicine, while promising, comes with significant risks that demand careful consideration. One of the most concerning aspects is the loss of autonomy that constant monitoring might bring. In a world where every heartbeat, hormone fluctuation, and calorie intake is tracked, individuals could feel trapped in a system that over-medicalizes daily life. Not every small deviation from a baseline is cause for alarm, but patients might find themselves overwhelmed with unnecessary interventions or nudges, leading to a perpetual sense of inadequacy or anxiety about their health. The psychological toll of being “optimized” every moment—always striving for a state of perfection dictated by algorithms—could create a culture of dependence and even erode the human experience of living freely.

The overreliance on technology is another pressing concern. What happens when the system fails? A device outage, a software glitch, or a malicious hack could disrupt the delicate ecosystem of precision medicine, leaving patients without their tailored medications or critical health data. More importantly, could this reliance diminish trust in human healthcare providers? If algorithms dictate treatments and override traditional medical intuition, we risk losing the irreplaceable human connection that underpins effective caregiving. Patients might begin to see doctors not as decision-makers but as implementers of machine-generated plans, potentially eroding the relationship of trust that has defined medicine for centuries.

Finally, pharmaceutical disruption presents a broader societal challenge. The advent of 3D-printed polypills could upend the traditional pharmaceutical industry, which relies on large-scale manufacturing and standardized dosing. While this disruption might bring innovation, it could also lead to fierce resistance from industry giants whose profits are threatened. The logistical backbone of drug distribution—pharmacies, supply chains, and even global drug manufacturers—would need to reinvent itself, a process fraught with risks, inefficiencies, and potential backlash. Policymakers will need to navigate these turbulent waters, balancing the promise of precision medicine with the stability of existing systems.

It’s important to note that several pharmaceutical companies are already studying this business model.

A Roadmap for Moving Forward

Several companies are at the forefront of developing 3D-printed pharmaceuticals, aiming to revolutionize personalized medicine:

• Aprecia Pharmaceuticals: In 2015, Aprecia introduced Spritam, the first FDA-approved 3D-printed drug designed to treat epilepsy. Utilizing their proprietary ZipDose® technology, Aprecia produces rapidly disintegrating formulations, enhancing patient adherence. The company continues to innovate in 3D printing for pharmaceuticals, exploring collaborations to expand its product offerings.
• FabRx: A UK-based enterprise, FabRx specializes in 3D printing personalized medications. Their Printlets® technology enables the creation of bespoke drug dosages and combinations tailored to individual patient needs. Notably, FabRx has developed personalized pills for children with rare metabolic disorders, optimizing treatments based on specific patient parameters.
• Merck Group: Global pharmaceutical leader Merck has ventured into 3D printing through collaborations aimed at developing and producing 3D-printed tablets. In partnership with AMCM, an EOS Group company, Merck focuses on creating tablets for clinical trials and eventual commercial manufacturing, exploring various 3D printing technologies to address challenges in solid-dose formulations.
• GlaxoSmithKline (GSK): GSK has engaged in research to integrate 3D printing into drug development, collaborating with companies like Stratasys to explore innovative drug delivery systems. Their efforts aim to leverage 3D printing for more efficient and personalized medication production.

These companies exemplify the pharmaceutical industry’s commitment to harnessing 3D printing technologies, striving to make personalized medicine more accessible and effective for patients worldwide.

To unlock the full potential of 3D-printed precision medicine while addressing its pitfalls, we need an actionable roadmap grounded in interdisciplinary collaboration. Scientists and engineers must work hand-in-hand with ethicists and policymakers to ensure that innovation is pursued responsibly. For example, bioengineers developing sensors for health monitoring need to consult with ethicists about the psychological impact of always-on surveillance, while legal experts draft policies to protect patient data from misuse. The convergence of these disciplines can provide the checks and balances necessary for building a sustainable healthcare ecosystem.

Central to this effort is the establishment of robust regulation and oversight. The global community must come together to create frameworks that address the unique challenges posed by 3D-printed drugs. Standards for printer accuracy, drug formulation, and patient safety must be universally recognized to ensure trust in this technology. Equally important is the regulation of AI-driven healthcare ecosystems, ensuring transparency in decision-making algorithms and safeguarding against biases that could harm patients. Without these guardrails, the promise of precision medicine could be undermined by mistrust and misuse.

Perhaps the most critical piece of the roadmap is addressing equity in access. The risk of precision medicine becoming a luxury for the wealthy is real, and it could exacerbate existing healthcare disparities. To prevent this, governments and innovators must prioritize accessibility, exploring subsidized models, public-private partnerships, and open-source solutions for the underlying technologies. The ultimate goal should be to democratize precision medicine, ensuring that its benefits extend to all, regardless of socioeconomic status.

Say goodbye to all your cabinets filled with pills.

Final Thoughts – A Pill for Humanity’s Future

Returning to the scenario of waking up to a personalized polypill, it’s worth reflecting on what this vision truly means for humanity. On one hand, the possibilities are exhilarating: lives saved through early intervention, chronic diseases managed with ease, and a new standard of health that adapts to each individual’s needs. On the other hand, this revolution carries profound societal implications, reshaping our understanding of health, autonomy, and even what it means to be human.

The dual-edged nature of this transformation demands caution. While precision medicine has the potential to redefine healthcare for the better, it also risks creating new forms of inequality, dependence, and ethical dilemmas. As we stand at the brink of this new era, the question is not whether we should embrace these technologies but how we can ensure they serve the common good.

The call to action is clear: we must balance innovation with responsibility, championing a vision of precision medicine that uplifts humanity as a whole. By doing so, we can turn the dream of personalized healthcare into a reality that benefits everyone—not just the privileged few. The pill for humanity’s future is within our grasp; it’s up to us to determine its impact.

The year 2023 marked the public debut of generative AI as a technological marvel. Systems like DALL-E 2 and GPT-3 captivated audiences by producing remarkably human-like synthetic content with just a few prompts. But as astonishing as these capabilities seem today, 2024 is likely to usher in even more seismic transformations as generative AI proliferates across industries.

Here are eight of the key trends that will be guiding the explosive growth of AI over the coming year.

1. Bigger, Better and Faster Foundation Models

Thus far, the raw scale of datasets and model parameters has proven crucial to the unprecedented capabilities exhibited by systems like GPT-3 and DALL-E 2. These models flaunt parameter counts in the hundreds of billions or trillions – a testament to the direct correlation between model size and performance.

It is very likely that 2024 will usher even bigger models like GPT-4, likely exceeding trillions or quadrillions of parameters, trained on vast corpora surpassing a trillion tokens. The relentless pace of progress in computational power, fueled by specialized AI accelerators and hyperscale cloud infrastructure, will facilitate training such behemoths.

However, the model scale alone does not guarantee better performance. We may see breakthroughs from innovations in model architecture, novel activation functions, sparse representations, increased depth, prompt programming, chain-of-thought training frameworks, reinforcement learning, and multimodal models that assimilate diverse data types.

Approaches like transfer learning – priming models on narrow tasks before general training – can also boost results. Techniques to reduce computational and environmental costs, like sharding models into smaller pieces for training, may supplement brute-force scaling.

Regardless of the exact techniques used, the unprecedented industry investment into foundation models makes it abundantly clear that 2024 will produce generative AI systems with exponentially greater capabilities than seen thus far. The dizzying pace of progress shows no signs of slowing down.

With each leap in foundation model prowess, the horizons of possible applications widen, too. GPT-4 could potentially unlock new frontiers like reliable voice interfaces, video and code generation, real-time translation, autonomous planning and discovery of knowledge. But such power also underlines the need for accountability and oversight frameworks to guide this technology’s impact ethically.

2. Election Meddling with AI: Navigating the Double-Edged Sword

Election seasons have always been rife with strategic communications, some transparent and others veiled. However, as we approach the pivotal leadership races in 2024 in major democracies like the USA, UK, and India, a new player enters the arena: generative AI. This powerful technology offers both promising opportunities and potential pitfalls in the realm of political discourse.

The dark side of generative AI in electoral contexts lies in its capacity to produce misinformation at an unprecedented scale and sophistication. Deepfakes, AI-generated videos that superimpose the likeness and voice of individuals onto existing footage, have evolved in quality, making it increasingly challenging for the average viewer to discern reality from fabrication. Imagine a scenario where a deepfake portrays a political candidate making controversial statements, sowing discord, and potentially swaying public opinion based on falsehoods. The implications are vast, potentially undermining trust in the democratic process and its players.

Beyond video manipulation, generative AI can be harnessed to craft vast amounts of propaganda, from misleading articles to biased social media posts. The sheer volume and speed at which this content can be disseminated could saturate information channels, making it harder for genuine news and facts to break through the noise.

However, every technology has its silver lining, and generative AI is no exception. In the hands of responsible political entities, it can be a tool to enhance and personalize campaign communications. For instance, AI can analyze vast amounts of data to understand the nuanced needs and concerns of different demographic groups. This could lead to tailored campaign messages that resonate more deeply with individual voters, ensuring that their specific concerns are addressed. Furthermore, AI can automate and optimize the outreach process, ensuring that campaign messages reach the right audiences at the right time.

Navigating the 2024 elections in the shadow of generative AI will require vigilance from both political entities and the general public. Media literacy and awareness campaigns can play a crucial role in educating voters about the potential manipulations they might encounter. Additionally, robust regulatory frameworks and technological solutions, like deepfake detection tools, can help mitigate the risks.

3. Widening the Horizons of Content Creation

While text and image generation has gained significant public attention thus far, 2024 is likely to see generative AI dramatically expand creative frontiers across diverse digital mediums.

In the video realm, consumer-facing tools will enable amateur creators to automatically edit footage, synthesize voiceovers, generate soundscapes, overlay visual effects, and weave compelling narratives. Complex video production pipelines, once accessible only to experts, will be democratized.

Generative 3D environments, VR and AR will also gain steam. World-building engines that automatically populate interactive landscapes, building interiors, and even entire metropolitan cityscapes with just text prompts are on the horizon.

In animation, AI-assisted techniques will expedite character design, motion synthesis, lip-syncing, scene choreography and rendering. Combined with the simulation of physics and materials, entire animations could be synthesized from scratch.

For audio, advances in AI narration, music generation, acoustics modeling, and mixing/mastering will unlock new modes of soundscape creation. Podcast and audiobook narration without real human voices is imminent.

Undergirding all these domains are powerful multimodal models that assimilate video, audio, speech, 3D environments, physics and language into a common representational framework – enabling holistic scene generation.

On the commercial front, generative AI will augment creatives across media production, gaming, architectural visualization, VFX and other artistic fields. Workflows enhanced by AI will enable professionals to ideate, prototype and refine content faster.

Together, these expansions will unlock new horizons of digital expression and human creativity while also raising important questions around copyright, data ethics and attribution. Guiding these tools responsibly promises to maximize generative AI’s benefits for society.

4. Reshaping Product Design and Manufacturing

The disruptive potential of generative AI extends far beyond just digital content creation. One physical domain ripe for transformation is industrial design and engineering of products.

Already, platforms like Autodesk, Revopoint, and nTopology are infusing generative AI to automate repetitive design tasks like topology optimization, component sizing, shape synthesis, and drafting. These tools can rapidly generate and simulate thousands of 3D design variations to accelerate ideation.

By leveraging physics simulations, robotic motion testing, and other analytics upstream in the design process, flaws can be caught early on. This promises to fundamentally reshape engineering workflows.

Combining generative design with agile manufacturing techniques like 3D printing, CNC machining, and adaptive robotics enables a completely new paradigm – bespoke products created on-demand and tailored to each customer’s needs.

Startups integrating design AI and on-demand fabrication could revolutionize the process of translating concepts into tangible products. We could see custom-manufactured goods compete with mass-produced ones.

This cycle of virtual prototyping, simulation, and custom fabrication promises to foster greater design experimentation and personalization. It could also enable localized and decentralized manufacturing.

However, the energy and material costs of on-demand fabrication warrant consideration to ensure sustainability. Workforce reskilling will also be crucial as these technologies transform engineering roles. But prudently steered, AI-enabled generative design could democratize access to customized products.

5. Reshaping Business Workflows with AI

Within enterprise environments, pre-trained generative models are already being deployed to streamline workflows from document drafting to customer support.

For content creation, tools like Jasper and Anthropic Claude can generate blogs, reports, emails, and other documents by converting brief outlines into fluent text. This promises to automate routine documentation.

In customer service, chatbots powered by dialogue models can handle common queries across sales, support, and HR, routing only complex cases to human agents. Conversational AI promises round-the-clock assistance.

Data processing workflows are being augmented by AI techniques like named entity recognition, topic modeling, summarization, and semantic search to extract insights from unstructured text and drive decisions.

Across functions from finance to operations, repetitive report generation, data entry, and analysis can be automated by training models on past examples. This frees up employee time for judgement-intensive work.

By 2024, upwards of 40% of business applications could integrate conversational AI interfaces to boost productivity and engagement. But fully capitalizing on AI’s potential requires deliberate efforts to re-engineer processes, data pipelines, and employee skills around AI integration.

Roles like prompt engineers, AI trainers, and model interpreters are rising in demand, requiring education and change management. Adopters who proactively reshape their operations to leverage AI will gain a competitive edge. But merely bolting on AI tools without a holistic integration strategy will squander their benefits.

6. Navigating the Changing Careers and Skills Landscape

As with past technological shifts, the ascent of generative AI promises to simultaneously displace certain jobs while creating new lucrative roles.

Positions involving highly repetitive and predictable tasks like data entry, document processing, and call center support are likely to face displacement from automated AI services. Proactive workforce planning and aid for affected workers will be critical.

However, roles leveraging uniquely human strengths like building trust, creativity, complex communication, and sound judgment within ambiguous contexts will remain irreplaceable.
Workers who can complement AI’s capabilities will thrive.

New positions like prompt engineers, AI trainers, model interpreters, and tool explainers are already rising in demand. Skilled communicators who can distill complex business needs into natural language instructions suited for AI will also see significant opportunities. Technical roles developing user interfaces that build confidence in AI systems will similarly grow.

Education and policy will need to emphasize these emerging skills while strengthening timeless human abilities like relationship-building, empathy, and holistic thinking. Life-long learning to stay ahead of AI’s evolving capabilities will be crucial.

Organizations that view their employees as partners in navigating this AI transition rather than costs to eventually eliminate will likely gain an edge through knowledge retention and human-AI collaboration.

With prudent planning, generative AI can drive positive workforce transformation. But neglecting to develop the human capital to extract AI’s full value risks misuse, distrust, and widening inequality.

7. Managing the Fallout of Disinformation

The rapid advance of generative AI does raise real concerns about its potential misuse to spread misinformation and manipulate public opinion online.

The capability to generate increasingly convincing images, videos, and text that are false yet appear real enables new avenues for fraud, propaganda, and coordinated disinformation campaigns. Pivotal events in 2024, like elections, could serve as testing grounds for deploying manipulative synthetic media on social platforms.

To manage this risk, social networks will need policies and technical systems to detect AI-generated content, label it distinctly from authentic user-created media, and limit its reach and virality where appropriate.

Standards will be needed around dataset ethics – training models on certain types of harmful or biased data must be prohibited. Transparency about training data and techniques will help build public trust.

Accountability mechanisms like maintaining detailed logs of generative model access and attributions to track propagation may deter malicious use. Platforms will need scalable oversight processes.

Public awareness campaigns explaining how AI can fabricate media will be crucial. Media literacy education teaching critical thinking skills helps inoculate society.

Policymakers may need to enact regulations mandating transparency and accountability around synthetic content. But a delicate balance is also required to nurture innovation.

Through prudent oversight and a collaborative approach between tech companies, lawmakers, media outlets and the public, the benefits of generative AI can be realized while safeguarding online trust and authenticity. But a proactive, ethical approach is imperative.

8. The Emergence of Self-Directed AI Systems

On the technology front, an important trend is the emergence of AI agents that act with increasing autonomy and reduced human guidance. This self-directed capability has profound implications.

Its roots can be seen in today’s unsupervised learning techniques like self-supervised training and contrastive learning, which allow models to learn patterns from unlabeled data. Models trained this way develop intrinsic representation capabilities.

Reinforcement learning further enables agents to optimize behaviors based on feedback signals like rewards and penalties without explicit instructions. In constrained environments like games, RL agents can exceed human performance.

Combining unsupervised pre-training with RL could enable agents to take purposeful, adaptive actions in more unstructured real-world settings. Think warehouse robots that optimize inventory organization or virtual assistants that take proactive steps to aid users.

Emergent coding techniques that translate high-level goals into executable code and simulations could accelerate self-directed AI. Agents may begin coding algorithms and environments to fulfill the objectives they are given.

Over the long run, extremely capable, self-directed systems could develop agency that is indifferent or contrary to human interests unless carefully constrained. Philosophical questions around AI ethics, oversight, controllability, and goal alignment warrant deep thought even today.

The seeds of self-directed AI already exist in today’s innovations. Prudently cultivating these technologies while aligning them to human values will require foresight from researchers, regulators and society. The autonomy genie cannot be put back into the bottle, so we must judiciously guide its capabilities as they unfold.

Final Thoughts

As we step into 2024, the breakneck pace of generative AI’s evolution shows no signs of slowing down. Its capabilities today seem almost magical but will become table stakes in short order. What we have witnessed so far is merely a prelude to this technology’s disruptive potential across every industry.

The unprecedented scale of investments into generative models and applications already exceeds the research budgets of most nations. This highlights how decisively some tech giants are betting on AI’s ascendance. Open-source ecosystems and startups are poised to drive equally exciting breakthroughs.

But with such power comes the responsibility to steer its influence prudently. As generative AI infiltrates our creative pursuits, business operations, public discourse and indeed daily lives, maintaining its societal benefit will require deliberate efforts.

Ethical considerations surrounding data sourcing, model transparency, system accountability and misuse prevention warrant urgent attention. Policies, norms and technical safeguards today will shape this technology’s trajectory for decades hence.

As citizens, we must develop our understanding of generative AI’s capabilities and limitations, shed our awe of its magic, and hold institutions deploying it accountable. Media literacy, as these synthetic creations blend increasingly seamlessly into our information diet, is crucial.

There are certainly risks to be mitigated proactively. But approached thoughtfully, generative AI can augment human creativity, efficiency and insight in wondrous ways. The extent of its lasting positive impact will come down to collective responsibility and wisdom.

The genie is undoubtedly out of the bottle, and the technology’s progress is unrelenting. 2024 promises to be a landmark year as generative AI’s transformation of society comes into fuller view. The actions we take today, as individuals and together, will write the human story of this historic technological flowering. There are causes for concern but also tremendous grounds for hope as we guide these transformative tools toward empowering our future.

While I started talking about 3D pill printers nearly ten years ago, today we are seeing incredible breakthroughs in personalized medicine emerging along two fronts:

• Diagnostic Breakthroughs, for example, with genetic, DNA, and molecular testing to uncover possible health threats, suggest optimal treatment pathways, and determine if further specialized tests are needed.
• Intervention Breakthroughs to customize care to the patient and yield a patient-based rather than a one-size-fits-all disease-based treatment protocol.

One of the most exciting and promising developments on the intervention side is the development of 3D-printed (additive manufacturing) pharmaceuticals. The promise for these products lies not only in the conventional manufacturing process but in the possibility of customizing the drugs in areas like dosage and release timing.

The pharmaceutical industry has come a long way from the days of crudely formulated drugs and doctors who basically guess what dosages are right for their patients.

If a particular pharmaceutical comes in the form of a 200 mg pill, doctors will prescribe 200, 400, or 600 mg doses when the right dose for an individual may be 87 mg, 341 mg, or 496 mg. With 3D printing, doctors can be far more precise.

Also, if the patient doesn’t tolerate an important drug well, doctors will have the option of customizing the pill, so the ingredients are released over an extended period of time.

Where We Stand Now

The U.S. Food & Drug Administration (FDA) has already approved the 3D printing of one drug, Aprecia Pharmaceutical’s Spritam, an anticonvulsant medication used for the treatment of seizures. With that approval, industry leaders see the floodgates opening. As 3D printing technology evolves and production costs come down, any pill or capsule that we swallow is now a candidate for this process and this kind of customization.

The FDA has also given preliminary approval to Eli Lilly to partner with Triastek, a Chinese pharmaceutical additive manufacturing company, to explore delivery mechanisms for two of its new medications. The two companies are investigating printed pill shapes and other excipient (non-medicinal) properties that promote the programmed or timed release of the drug’s active ingredients.

In addition to Aprecia and Eli Lilly, three other drug companies, GlaxoSmithKline, Merck, and FabRx, are also actively pushing into this market.

Globally, the market for 3D-printed drugs is predicted to grow by 15% over the next six years, reaching more than $2 billion by 2027.

We’re on the verge of a 3D-printed pharmaceutical industry where precisely measured doses are easy to create and where multiple drugs in varying doses can be combined into a single pill. Flavors and colors will be customized as well.

Eight Advantages of Printed Pharmaceuticals

Personalized health care is clearly one of the primary benefits of 3D-printed oral medications. But I see at least eight additional reasons this technology will be a game changer.

1. Specialized Drugs

It will enable small-batch printing of specialty drugs for rare or “orphan” diseases, the kind of drugs that pharmaceutical companies tend to sidestep due to low volume and profitability. The technology will also be the ideal way to produce small quantities of drugs for clinical trials in which variable doses need to be tested.

2. Reduced Inventory

Hospitals will be able to print specialized and personalized drugs onsite, reducing the need for stockpiling and providing nearly immediate access to specialty drugs they may not have on hand.

3. Local Production Advantages

In addition to hospitals, pharmacies will be in a position to print prescribed drugs for their customers. The distribution process for many drugs will be shortened as we bypass drug wholesalers for many specialized drugs.

4. Shorter Supply Chain

Locally produced 3D-printed drugs won’t be subject to supply chain constraints. Today, many of our drugs are formulated overseas and then packaged there. That equates to a lot of shipping and quality control steps.

5. Workarounds for Disruptions

If a drug manufacturer needs to temporarily close its facility for any reason, 3D printing can fill the supply gap.

6. Improved Drug Safety

Aspects of drug safety can be improved with local production since there will be less opportunity for counterfeit drugs to be introduced into the distribution process. Costs related to maintaining the required documented pedigree of the drug will be reduced as well.

7. Efficient Use of Raw Materials

3D printing of any item, whether it’s a house, pair of shoes, or a pharmaceutical drug, makes far more efficient use of the raw materials involved. Less waste in drug production means far better use of valuable chemical ingredients.

8. Reduced Cost to End User

Most of these benefits – including the shorter distribution chain, reduced expenses for tracking drug pedigrees, less production waste, and localized production – along with continued advances in 3D printing technology, has the potential to significantly reduce the cost of drugs for the end user.

Barriers We Still Need to Overcome with 3D-Printed Drugs

Even though I just painted a rather promising future for this industry, we’ll still need to resolve certain challenges that will come with widespread 3D drug printing.

• Bad Actors

  As with any technological breakthrough, we’ll need to anticipate how 3D drug printing could be abused by bad actors. The technology will enable drug dealers to manufacture illicit narcotics and it could empower counterfeiters to print fake drugs without active ingredients or with the wrong/dangerous ingredients.

• Revised Regulatory Processes

  We’ll need to revise our drug manufacturing regulatory process, shifting to approving multiple local production sites rather than primary manufacturing plants. The FDA will also need to address matters related to personalized dosing and release profiles. That means regulators will have to focus on additive manufacturing equipment, processes, and quality assurance of the printing ingredients – not a small shift for this large bureaucracy. To their credit, though, the FDA is already working with the National Institute of Standards and Technology to develop guidelines for 3D drug production.

• Industry Disruptions

  The pharmaceutical manufacturing industry will likely raise regulatory and legal barriers to this widespread practice since it threatens the industry’s markups and monopolies. Some will shift to becoming suppliers of chemical ingredients rather than manufacturers of finished pills and capsules.

Over time, we’ll overcome these hurdles so that the benefits of customized, 3D-printed pharmaceuticals will be available for everyone. The FDA will reach a tipping point so that approvals for these processes and products will become more routine while remaining thorough.

And as we add more and more sensors to our bodies, the linkage between personalized diagnostics and personalized pharmacological treatment will become even closer and … well… even more personalized.

Challenges in the construction industry, including a declining workforce and the cost of materials, combined with some incredible technology and manufacturing breakthroughs, are changing today’s construction sites in ways that will make them unrecognizable in the future. The three trends making the most impact are: modular construction, 3D printing construction, and robotic bricklaying.

Modular Construction

Prefabrication is a broad term that describes the practice of building all or portions of a home or commercial building off-site – maybe even in another state or country. The components are transported to the construction site for incorporation into the structure or to make up the structure itself.

The most intriguing of these prefab options is “permanent modular construction,” or PMC. Specialized prefabrication companies can build rooms or entire suites offsite, complete with pipes, fixtures, wiring, tile, and countertops. They’re shipped to the construction site by truck and off-loaded with massive cranes. The modules are held in place while workers scramble to connect them with other elements of the structure or stack them on top of or next to another module.

It’s not quite snap in place but it’s not too far off.

While modular construction represents around 4% of commercial and residential projects in the U.S., that number is already significantly higher in China, Japan, and some European countries.

Modular projects offer incredible efficiencies and implications for quality. Fabricating modules at a climate-controlled indoor site transforms the work into more of a repeatable factory job than a craftsman task. Plus, in order to withstand the rigors of the transporting and off-loading steps, modules tend to be built to sturdier specifications, which make the resulting buildings better able to survive the worst that nature can throw at them.

A recent industry analysis found that developers see the most promise for the modular technique with healthcare facilities, hotels/motels, multifamily residences, schools and colleges, and low-rise offices.

3D Printing Construction

Before dismissing the idea of a “concrete house,” check out this one by a builder in New York. The company’s robotic construction system built 40% of the structure – the windows and walls – before finish workers came in to take care of the rest. The final cost of the house was approximately 20% less than a comparable, traditionally built home.

The technical term for 3-D printing is “additive manufacturing”. Framing a 2,000 square foot house using this technology can take as little as three days. 3-D builders are moving beyond the use of normal concrete to reinforced composites that can further reduce the price and make the homes even more secure from fire, pests, water damage, and mold.

The overall cost reduction of 10-50%, faster construction speed, and increased durability makes 3-D printed homes very attractive as affordable starter homes.

Even greater efficiencies are possible when the printing is combined with modular construction. This planned community in California will have 3-D printed homes that are built in a fabrication facility and then shipped to their new neighborhood.

Printed homes can be designed and constructed in all styles, from traditional to downright space age, as with these futuristic-looking styles.

From an environmental perspective, additive manufacture of homes is a win as well, since the process doesn’t produce any scrap.

3-D homes could be ideal in remote, impoverished locations around the world. If the truck and supplies can be brought in, there’s little need for too many more construction
specialists, especially if the designs are quite simple.

Robotic Bricklaying Construction

What would be more futuristic than a competition between a robotic arm that’s printing a wall vs. a robotic arm that’s building a brick wall? The concepts are similar – the layer-by-layer construction of the interior and exterior framing guided by pre-programmed design plans.

Today’s truck-based, robotic arms can load, cut, route, and place bricks, framing a house in as little as two days. Human bricklayers lay 300-500 pieces per day on average. In contrast, the leading robotics alternatives can place 200 much larger bricks per hour – and that’s expected to increase to 1,000 in future models. These robots also apply a special mortar or adhesive that dries faster than standard mortar.

Just like the other construction technology solutions, robotic bricklaying is evolving and making tremendous strides in improved speed, safety, and quality. The benefits and economies related to this approach to bricklaying are even greater when the technique is applied to multi-story structures.

The Future of Housing

Residential and commercial construction in the U.S. is a $1.6 trillion industry. Hundreds of thousands of construction workers were laid off during COVID and the Census Bureau estimates that 60% of them won’t return, in spite of the expected resurgence of the industry in 2021.

In the U.S., state and local budgets have been squeezed thanks to COVID economic impacts, so less funding is available to subsidize affordable housing projects. And with the hot housing market, more and more people are being priced out of starter homes.

Modular assembled, 3D printed, and robot built homes can bring down housing costs and help address both of those pressing societal issues as we move into the future, leaving plenty of room and demand for all three of these technologies.