ReviewRegenerative biomaterials2016
Critical questions in development of targeted nanoparticle therapeutics.
Review in Regenerative biomaterials, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed, 29 citations in OpenAlex.
- Current and emerging approaches to manage chronic inflammatory gut disorders.Frontiers in cellular and infection microbiology · 2026Review
- Biomaterials for neuroengineering: applications and challenges.Regenerative biomaterials · 2025Review
- Transformative Impact of Nanocarrier-Mediated Drug Delivery: Overcoming Biological Barriers and Expanding Therapeutic Horizons.Small science · 2024Article
- PEG-Polymeric Nanocarriers Alleviate the Immunosuppressive Effects of Free 4-Thiazolidinone-Based Chemotherapeutics on T Lymphocyte Function and Cytokine Production.International journal of nanomedicine · 2024Article
- Hydrogen-bond super-amphiphile based drug delivery system: design, synthesis, and biological evaluation.RSC advances · 2022Article
- Soft-Nanoparticle Functionalization of Natural Hydrogels for Tissue Engineering Applications.Advanced healthcare materials · 2019Review
- Re-evaluating the importance of carbohydrates as regenerative biomaterials.Regenerative biomaterials · 2019Review
- Walking the line: The fate of nanomaterials at biological barriers.Biomaterials · 2018Review
- Make It Simple: (SR-A1+TLR7) Macrophage Targeted NANOarchaeosomes.Frontiers in bioengineering and biotechnology · 2018Article
- Multimodal imaging of the receptor for advanced glycation end-products with molecularly targeted nanoparticles.Theranostics · 2018Article
- Dendrimers for Ocular Drug Delivery.Canadian journal of chemistry · 2017Article
- The Targeted Antitumor Effects of C- PC/CMC-CD59sp Nanoparticles on HeLa CellsJournal of Cancer · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
One of the fourteen Grand Challenges for Engineering articulated by the US National Academy of Engineering is 'Engineer Better Medicines'. Although there are many ways that better medicines could be engineered, one of the most promising ideas is to improve our ability to deliver the therapeutic molecule more precisely to the desired target. Most conventional drug delivery methods (oral absorption, intravenous infusion etc.) result in systemic exposure to the therapeutic molecule, which places severe constraints on the types of molecules that can be used. A molecule administered by systemic delivery must be effective at low concentrations in the target tissue, yet safe everywhere else in the body. If drug carriers could be developed to deliver therapeutic molecules selectively to the desired target, it should be possible to greatly improve safety and efficacy of therapy. Nanoparticles (and related nanostructures, such as liposomes, nanoemulsions, micelles and dendrimers) are an attractive drug carrier concept because they can be made from a variety of materials engineered to have properties that allow loading and precise delivery of bound therapeutic molecules. The field of targeted nanoparticles has been extraordinarily active in the academic realm, with thousands of articles published over the last few years. Many of these publications seem to demonstrate very promising results in in vitro studies and even in animal models. In addition, a handful of human clinical trials are in progress. Yet, the biopharmaceutical industry has been relatively slow to make major investments in targeted nanoparticle development programs, despite a clear desire to introduce innovative new therapies to the market. What is the reason for such caution? Some degree of caution is no doubt due to the use of novel materials and the unproven nature of targeted nanoparticle technology, but many other unproven technologies have generated intense interest at various times. We believe that the major barrier to the exploration of nanoparticles is because they are so complex. The very design flexibility that makes the nanoparticle approach attractive also makes it challenging. Fortunately, continuing progress in experimental tools has greatly improved the ability to study biology and potential interventions at a nanoscale. Thus, it is increasingly possible to answer detailed questions about how nanoparticles can and should work. However, a detailed understanding at the mechanistic level is only the beginning. Any new medicine must not only work at the molecular level, but must also be manufactured reproducibly at scale and proven in the clinic. New materials will require new methods at all scales. The purpose of this short article is to focus on a set of questions that are being asked in the large biopharmaceutical companies and that must be answered if targeted nanoparticles are to become the medicines of the 21st century.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.