Engineers are often tempted to come up with complex and convoluted designs to tackle major health challenges. In the ever-evolving landscape of bioengineering, innovation often conjures images of complexity and high-tech sophistication. However, some of the most impactful breakthroughs have come from simple solutions that leverage core engineering principles, such as scalability, cost-effectiveness and ease-of-use.

“some of the most impactful breakthroughs have come from simple solutions that leverage core engineering principles, such as scalability, cost-effectiveness and ease-of-use”

A prominent example is the success of lipid nanoparticle (LNP) formulations for delivering mRNA vaccines against COVID-19. In their quest to improve targeting, stability and biocompatibility, the drug delivery and nanomedicine fields had often leaned towards designing highly complex architectures and formulations. However, the efficacy of these relatively simple LNP platforms in enabling systemic mRNA delivery may have catalysed a shift in the focus of nanomedicine research towards simpler and more scalable platform systems.

The ‘how complex is complex enough’ debate can also be extended to the engineering of hydrogel and biomaterials-based platforms for biomedical applications. In this issue, Nicholas A. Peppas and team discuss how the simplicity and versatility of clinically established hydrogels can be leveraged in a model-driven modular design fashion. This approach could help to overcome barriers to the clinical translation of hydrogels by simplifying the design process using application-focused design criteria, multi-property modelling, modular hydrogel components and iterative development.

This design- and solution-oriented engineering mind-set (as opposed to more discovery-oriented fundamental disciplines)1 can be applied to even more sophisticated and multicomponent technologies, such as brain-machine interfaces. For example, Schalk et al.2 argue that, for neurotechnologies to be clinically and commercially viable, overemphasizing the optimization of individual components could be detrimental to translation. In other words, any individual component does not need to be perfect, but instead perform at a ‘satisfactory’ level in which the system ‘as-a-whole’ provides enough incremental health benefits, financial incentives, practicality and reliability compared with the standard-of-care.

Frugal technologies are great examples of where simple designs have rapidly advanced clinical care, such as low-cost prosthetics and assistive devices3, paper-based lateral flow assays used at the point-of-care3,4, low-cost infant warmers or the now well-established fingerstick-free continuous glucose-monitoring systems. Even in the cutting-edge field of bioelectronics, simplicity is being pursued by the design of flexible, biocompatible sensors and actuators that operate without a battery or wired connection by harvesting energy from the body5.

Although simplicity and modular platform technologies are attractive for scalable and accessible biomedical solutions, certain medical challenges require highly customized and patient-specific interventions. For example, bone and cartilage grafts should accurately match the complex 3D architecture of the patient’s tissue defect. In rare genetic disorders and disease subtypes, the diversity of mutations and patient genotypes necessitate personalized gene-editing strategies, such as custom-engineered vectors, tailored to each individual’s genetic profile. Thus, although simplicity accelerates innovation, treatments for certain unmet clinical needs may require bioengineers to purposefully embrace technological complexity tailored to the genetic, biological and anatomical intricacies of individual patients.

Nonetheless, global health benefits from the ease-of-use, cost-effectiveness and transferability provided by simple designs, which are inherently more scalable and more likely to be adopted at the community level. Therefore, before diving into the design of a new biomaterial, delivery system or medical device, one should ask (and answer) the question of ‘how complex is complex enough’ for the intended application.