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Nanodiamonds: The intersection of nanotechnology, drug development, and personalized medicine.

Ho D, Wang CH, Chow EK - Sci Adv (2015)

Bottom Line: These barriers include drug resistance leading to suboptimal intratumoral retention, poor circulation times resulting in decreased efficacy, and off-target toxicity, among others.The application of PPM-DD to rapidly identify globally optimized drug combinations successfully addressed a pervasive challenge confronting all aspects of drug development, both nano and non-nano.How this platform can accelerate combinatorial nanomedicine and the broader pharmaceutical industry toward unprecedented clinical impact will also be discussed.

View Article: PubMed Central - PubMed

Affiliation: Division of Oral Biology and Medicine, University of California, Los Angeles (UCLA) School of Dentistry, Los Angeles, CA 90095, USA. ; Department of Bioengineering, UCLA School of Engineering and Applied Science, Los Angeles, CA 90095, USA. ; The Jane and Jerry Weintraub Center for Reconstructive Biotechnology, UCLA School of Dentistry, Los Angeles, CA 90095, USA. ; California NanoSystems Institute, UCLA, Los Angeles, CA 90095, USA. ; Jonsson Comprehensive Cancer Center, UCLA, Los Angeles, CA 90095, USA.

ABSTRACT
The implementation of nanomedicine in cellular, preclinical, and clinical studies has led to exciting advances ranging from fundamental to translational, particularly in the field of cancer. Many of the current barriers in cancer treatment are being successfully addressed using nanotechnology-modified compounds. These barriers include drug resistance leading to suboptimal intratumoral retention, poor circulation times resulting in decreased efficacy, and off-target toxicity, among others. The first clinical nanomedicine advances to overcome these issues were based on monotherapy, where small-molecule and nucleic acid delivery demonstrated substantial improvements over unmodified drug administration. Recent preclinical studies have shown that combination nanotherapies, composed of either multiple classes of nanomaterials or a single nanoplatform functionalized with several therapeutic agents, can image and treat tumors with improved efficacy over single-compound delivery. Among the many promising nanomaterials that are being developed, nanodiamonds have received increasing attention because of the unique chemical-mechanical properties on their faceted surfaces. More recently, nanodiamond-based drug delivery has been included in the rational and systematic design of optimal therapeutic combinations using an implicitly de-risked drug development platform technology, termed Phenotypic Personalized Medicine-Drug Development (PPM-DD). The application of PPM-DD to rapidly identify globally optimized drug combinations successfully addressed a pervasive challenge confronting all aspects of drug development, both nano and non-nano. This review will examine various nanomaterials and the use of PPM-DD to optimize the efficacy and safety of current and future cancer treatment. How this platform can accelerate combinatorial nanomedicine and the broader pharmaceutical industry toward unprecedented clinical impact will also be discussed.

No MeSH data available.


Related in: MedlinePlus

PPM-DD–optimized drug combinations against hepatic cancers.(A) Hepatic cancer cells, such as Hep3B, exhibit enhanced uptake of glucose and glucose analogs (2-NBDG) compared to normal hepatocytes (THLE-2) and other hepatic cancer cells (Bel-7402). (B) Inhibition of hepatic cancer cell proliferation by PPM-DD–optimized two-drug (D1) and three-drug (D2) combinations were compared to PPM-DD–derived nonsignificant combinations (D3 and D4) in vitro. (C) Response surface plots of predicted outputs after ZM 449829 and HA-1004·2HCl reveal a synergistic relationship between the two drugs. Figures reprinted with permission from SAGE Publications.
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Figure 5: PPM-DD–optimized drug combinations against hepatic cancers.(A) Hepatic cancer cells, such as Hep3B, exhibit enhanced uptake of glucose and glucose analogs (2-NBDG) compared to normal hepatocytes (THLE-2) and other hepatic cancer cells (Bel-7402). (B) Inhibition of hepatic cancer cell proliferation by PPM-DD–optimized two-drug (D1) and three-drug (D2) combinations were compared to PPM-DD–derived nonsignificant combinations (D3 and D4) in vitro. (C) Response surface plots of predicted outputs after ZM 449829 and HA-1004·2HCl reveal a synergistic relationship between the two drugs. Figures reprinted with permission from SAGE Publications.

Mentions: Another recent study has demonstrated the capacity to use phenotypic data to pinpoint optimal drug combinations that maximize therapeutic efficacy while minimizing adverse effects. The phenotype-based experiments were performed for hepatic cancers and normal hepatocytes, and they revealed novel combinations of glucose metabolism inhibitors through phenotypic-based experiments without the need for previous mechanistic information (Fig. 5) (124). Increased glucose uptake and reprogramming of cellular energy metabolism, the Warburg effect, are hallmarks of many cancers, including hepatic cancers, and linked to tumor progression and poorer outcome (125–127). The key mechanisms that are required for enhanced glucose metabolism–mediated tumor progression are often complex and thus difficult to target therapeutically by traditional drug development methods (128). After a multiparameter high-content screen to identify glucose metabolism inhibitors that also specifically inhibit hepatic cancer cell proliferation but have minimal effects on normal hepatocytes, PPM-DD was implemented to identify optimal therapeutic combinations. Using a minimal number of experimental combinations, this study was able to identify both synergistic and antagonistic drug interactions in two-drug and three-drug combinations that effectively killed hepatic cancer cells through inhibition of glucose metabolism. Optimal drug combinations involved phenotypically identified synergistic drugs that inhibit distinct signaling pathways, such as the Janus kinase 3 (JAK3) and cyclic adenosine monophosphate–dependent protein kinase (PKA)/ cyclic guanosine monophosphate–dependent protein kinase (PKG) pathways, which were not previously known to be involved in hepatic cancer glucose metabolism. As such, this platform not only optimized drug combinations in a mechanism-independent manner but also identified previously unreported druggable molecular mechanisms that synergistically contribute to tumor progression.


Nanodiamonds: The intersection of nanotechnology, drug development, and personalized medicine.

Ho D, Wang CH, Chow EK - Sci Adv (2015)

PPM-DD–optimized drug combinations against hepatic cancers.(A) Hepatic cancer cells, such as Hep3B, exhibit enhanced uptake of glucose and glucose analogs (2-NBDG) compared to normal hepatocytes (THLE-2) and other hepatic cancer cells (Bel-7402). (B) Inhibition of hepatic cancer cell proliferation by PPM-DD–optimized two-drug (D1) and three-drug (D2) combinations were compared to PPM-DD–derived nonsignificant combinations (D3 and D4) in vitro. (C) Response surface plots of predicted outputs after ZM 449829 and HA-1004·2HCl reveal a synergistic relationship between the two drugs. Figures reprinted with permission from SAGE Publications.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4643796&req=5

Figure 5: PPM-DD–optimized drug combinations against hepatic cancers.(A) Hepatic cancer cells, such as Hep3B, exhibit enhanced uptake of glucose and glucose analogs (2-NBDG) compared to normal hepatocytes (THLE-2) and other hepatic cancer cells (Bel-7402). (B) Inhibition of hepatic cancer cell proliferation by PPM-DD–optimized two-drug (D1) and three-drug (D2) combinations were compared to PPM-DD–derived nonsignificant combinations (D3 and D4) in vitro. (C) Response surface plots of predicted outputs after ZM 449829 and HA-1004·2HCl reveal a synergistic relationship between the two drugs. Figures reprinted with permission from SAGE Publications.
Mentions: Another recent study has demonstrated the capacity to use phenotypic data to pinpoint optimal drug combinations that maximize therapeutic efficacy while minimizing adverse effects. The phenotype-based experiments were performed for hepatic cancers and normal hepatocytes, and they revealed novel combinations of glucose metabolism inhibitors through phenotypic-based experiments without the need for previous mechanistic information (Fig. 5) (124). Increased glucose uptake and reprogramming of cellular energy metabolism, the Warburg effect, are hallmarks of many cancers, including hepatic cancers, and linked to tumor progression and poorer outcome (125–127). The key mechanisms that are required for enhanced glucose metabolism–mediated tumor progression are often complex and thus difficult to target therapeutically by traditional drug development methods (128). After a multiparameter high-content screen to identify glucose metabolism inhibitors that also specifically inhibit hepatic cancer cell proliferation but have minimal effects on normal hepatocytes, PPM-DD was implemented to identify optimal therapeutic combinations. Using a minimal number of experimental combinations, this study was able to identify both synergistic and antagonistic drug interactions in two-drug and three-drug combinations that effectively killed hepatic cancer cells through inhibition of glucose metabolism. Optimal drug combinations involved phenotypically identified synergistic drugs that inhibit distinct signaling pathways, such as the Janus kinase 3 (JAK3) and cyclic adenosine monophosphate–dependent protein kinase (PKA)/ cyclic guanosine monophosphate–dependent protein kinase (PKG) pathways, which were not previously known to be involved in hepatic cancer glucose metabolism. As such, this platform not only optimized drug combinations in a mechanism-independent manner but also identified previously unreported druggable molecular mechanisms that synergistically contribute to tumor progression.

Bottom Line: These barriers include drug resistance leading to suboptimal intratumoral retention, poor circulation times resulting in decreased efficacy, and off-target toxicity, among others.The application of PPM-DD to rapidly identify globally optimized drug combinations successfully addressed a pervasive challenge confronting all aspects of drug development, both nano and non-nano.How this platform can accelerate combinatorial nanomedicine and the broader pharmaceutical industry toward unprecedented clinical impact will also be discussed.

View Article: PubMed Central - PubMed

Affiliation: Division of Oral Biology and Medicine, University of California, Los Angeles (UCLA) School of Dentistry, Los Angeles, CA 90095, USA. ; Department of Bioengineering, UCLA School of Engineering and Applied Science, Los Angeles, CA 90095, USA. ; The Jane and Jerry Weintraub Center for Reconstructive Biotechnology, UCLA School of Dentistry, Los Angeles, CA 90095, USA. ; California NanoSystems Institute, UCLA, Los Angeles, CA 90095, USA. ; Jonsson Comprehensive Cancer Center, UCLA, Los Angeles, CA 90095, USA.

ABSTRACT
The implementation of nanomedicine in cellular, preclinical, and clinical studies has led to exciting advances ranging from fundamental to translational, particularly in the field of cancer. Many of the current barriers in cancer treatment are being successfully addressed using nanotechnology-modified compounds. These barriers include drug resistance leading to suboptimal intratumoral retention, poor circulation times resulting in decreased efficacy, and off-target toxicity, among others. The first clinical nanomedicine advances to overcome these issues were based on monotherapy, where small-molecule and nucleic acid delivery demonstrated substantial improvements over unmodified drug administration. Recent preclinical studies have shown that combination nanotherapies, composed of either multiple classes of nanomaterials or a single nanoplatform functionalized with several therapeutic agents, can image and treat tumors with improved efficacy over single-compound delivery. Among the many promising nanomaterials that are being developed, nanodiamonds have received increasing attention because of the unique chemical-mechanical properties on their faceted surfaces. More recently, nanodiamond-based drug delivery has been included in the rational and systematic design of optimal therapeutic combinations using an implicitly de-risked drug development platform technology, termed Phenotypic Personalized Medicine-Drug Development (PPM-DD). The application of PPM-DD to rapidly identify globally optimized drug combinations successfully addressed a pervasive challenge confronting all aspects of drug development, both nano and non-nano. This review will examine various nanomaterials and the use of PPM-DD to optimize the efficacy and safety of current and future cancer treatment. How this platform can accelerate combinatorial nanomedicine and the broader pharmaceutical industry toward unprecedented clinical impact will also be discussed.

No MeSH data available.


Related in: MedlinePlus