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Research Programs
Drug Development, Cancer NanoMedicine, Cancer Vaccine, Pharmacokinetics
1. Why 90% drug development fails and how to improve it? (PPT Slides, Video Recording)
This project aims to improve drug development success through the STAR system (structure-tissue/cell selectivity-activity-relationship) by addressing the 90% failure rate for immuno-oncology drugs.
Development of one successful drug typically takes 10-15 years and costs $1-2 billion. Despite significant improvement in each step of drug development using hundreds strategies/criteria, 90% drug development fails from Phase I to Phase III trials. Adding more criteria without eliminating non-essential ones is impractical and may fall into “survivorship bias” trap. The 90% failures is compounded by multiple factors, which include poor disease target validation, poor translation from preclinical animal models to patients, genetic and epigenetic alterations of disease targets, disease heterogeneity, and poor clinical trial design. However, one major deficiency is not adequately addressed, that is, suboptimal or wrong drug candidates, with insufficient drug target validation, have been selected to enter clinical trials. If this deficiency is not addressed, all other efforts may not overcome the 90% drug development failures.
The current drug candidate selection process overlooks the following three inter-dependent factors, which misguide drug candidate selection, mis-balance clinical dose/efficacy/safety, lead to high clinical failures, or poor efficacy/high toxicity of approved drugs: (1) Current drug candidate selection from in vitro target binding IC50s overlooks potency/specificity (PS) to on/off-targets determining efficacy in disease tissue at relevant clinical dose. (2) Current drug candidate selection from drug-like property criteria overlooks tissue/cell selectivity (TS) influencing adverse effects (on/off-target toxicity) in normal organs at relevant clinical dose. (3) Clinical dose cannot be optimized to balance clinical efficacy/safety due to the overlooked optimization of in vivo potency/specificity and tissue/cell selectivity, while extensive GLP animal toxicity testing is not predictive for clinical adverse effects (on/off-target toxicity) at therapeutic dose.
We introduce the STAR system (structure-tissue/cell selectivity-activity relationship), which categorizes drugs into four classes based above three factors. STAR system prioritizes STAR class I drugs with high clinical success potential, contrasting with the current emphasis on class II/IV drugs with high failure rates.
We are currently using STAR system to optimize PI3K inhibitors and Sting agonists for cancer immunotherapy and JAK inhibitors for treating inflammatory bowel disease.
Latest manuscripts:
Why 90% of Clinical Drug Development Fails and How to Improve It? Duxin Sun, Wei Gao, Hongxiang Hu, Simon Zhou. Acta Pharmaceutic Sinica B, 2022, 12, 3049
Dual Targeting of STING and PI3Kγ Eliminates Regulatory B Cells to Overcome STING Resistance for Pancreatic Cancer Immunotherapy. Chengyi Li, Shuai Mao, Hongyi Zhao, Miao He, Meilin Wang, Zhongwei Liu, Hanning Wen, Zhixin Yu, Bo Wen, Mahamadou Djibo, Jinsong Tao, Yingzi Bu, Wei Gao, Duxin Sun (Under review in Nature Cancer 2024). bioRxiv doi: https://doi.org/10.1101/2024.02.14.580378
A gastrointestinal (GI) locally-activating Janus Kinae (JAK) inhibitor to treat ulcerative colitis. Yingzi Bu, Mohamed Dit Mady Traore, Luchen Zhang, Lu Wang, Zhongwei Liu, Duxin Sun. J Biol Chem, 2023, DOI:https://doi.org/10.1016/j.jbc.2023.105467
CoGT: Ensemble Machine Learning Method and Its Application on JAK Inhibitor Discovery. Yingzi Bu, Ruoxi Gao, Bohan Zhang, Luchen Zhang, and Duxin Sun. ACS Omega, 2023, 2023, 8, 14, 13232
Structure-Tissue Exposure/Selectivity Relationship (STR) Correlates with Clinical Efficacy/Safety. Wei Gao, Hongxiang Hu, Lipeng Dai, Miao He, Hebao Yuan, Huixia Zhang, Jinhui Liao, Bo Wen, Yan Li, Maria Palmisano, Mohamed Dit Mady Traore, Simon Zhou, Duxin Sun. Acta Pharmaceutic Sinica B, 2022, 12, 2462
2. Why most anticancer nanomedicines do not enhance clinical efficacy and how to improve it?
This project develops a drug/nanocarrier-specific anticancer nanomedicines to enhance their clinical efficacy and improve clinical success for cancer immunotherapy
Anticancer nanomedicines hope to act like biological missiles targeting tumors by (1) utilizing the enhanced permeability and retention (EPR) effect for increasing accumulation in tumors to improve efficacy, and (2) maintaining long bloodstream circulation for reducing accumulation in healthy organs to minimize toxicity. However, despite their outstanding efficacy in preclinical animal cancer models, most anticancer nanomedicines have not demonstrated superior clinical efficacy, sparking a decade long debate on current design strategies.
We found two key issues affecting their clinical efficacy: (1) EPR, while present in all animal and human tumors, may not always lead to the increased nanomedicine accumulation compared to free drugs depending on cancer models, (2) long circulation may reduce nanomedicine clearance by the mononuclear phagocyte system (MPS), but could negatively affect efficacy and alter, rather than reduce, toxicity.
We propose a drug/nanocarrier-specific nanomedicine design strategy to improve their clinical success: (1) Cancer-specific, identifying features of cancer types that can be used for targeted drug delivery; (2) Cell-specific, understanding the cell types to which drugs need to be delivered; (3) Drug-specific, identifying the intrinsic shortcomings of the delivered drugs that need to be overcome; and (4) Nanocarrier-specific, evaluating specific nanocarriers to overcome the specific limitations of the delivered drugs.
We are employing these new strategies to design albumin based nanomedicines of PI3K inhibitors and Sting agonists for cancer immunotherapy of various type of cancers.
The latest papers or manuscripts
What Went Wrong with Anticancer Nanomedicine Design and How to Make It Right. Sun D, Zhou S, Gao W. ACS Nano. 2020 Oct 27;14(10):12281-12290.
Reappraisal of anticancer nanomedicine design criteria in three types of preclinical cancer models for better clinical translation. Luan X, Yuan H, Song Y, Hu H, Wen B, He M, Zhang H, Li Y, Li F, Shu P, Burnett JP, Truchan N, Palmisano M, Pai MP, Zhou S, Gao W, Sun D. Biomaterials. 2021 Aug;275:120910.
Albumin nanoparticle containing a PI3Kγ inhibitor and paclitaxel in combination with α-PD1 induces tumor remission of breast cancer in mice. Yudong Song, Luke Bugada, Ruiting Li, Hongxiang Hu, Luchen Zhang, Chengyi Li, Hebao Yuan, Krishani Rajanayake, Nathan Truchan, Fei Wen, Wei Gao, and Duxin Sun. Science Translational Medicine, 2022, 14 (643): onlineDOI: 10.1126/scitranslmed.abl3649
3. Why most cancer vaccines only achieve short-term efficacy and how to improve it?
This project is focused on developing a cancer vaccine to achieve long-term tumor remission by promoting B/CD4 T cell crosstalk.
While current cancer vaccines, activating T cell immunity, have shown promising anticancer effects in melanoma, their efficacy in treating other types of cancer remains limited. In contrast, the role of B cell immunity in cancer vaccine design has been a topic of debate. Recent clinical studies, however, suggest that activating B cell immunity, particularly the interaction between B cells and CD4 T cells, is crucial for the long-lasting anticancer efficacy of immunotherapy. To address this, we have developed a virus antigen cluster mimicry nanovaccine (VAMVax), which enhances B cell and CD4 T cell cross-talk, to achieve long-term tumor remission in HER2-positive breast cancer.
The latest manuscript
Antigen-Clustered Nanovaccine Achieves Long-Term Tumor Remission by Promoting B/CD 4 T Cell Crosstalk. Chengyi Li, Ryan Clauson, Luke F. Bugada, Bing He, Hongwei Chen, Hongxiang Hu, Polina Chuikov, Ke Fang, Brett D. Hill, Syed M. Rizvi, Yudong Song, Kai Sun, Daniel Huynh, Marilia Cascalho, Lana Garmire, Leo Yu Lei, Irina Grigorova, Fei Wen, Wei Gao, Duxin Sun. ACS Nano 2024, March 21, in press.
4. What are the differences of microbiome, bile salts, and drug release in different regions of human GI tract?
This project investigates the variations in the microbiome, bile salts, and drug release within the human stomach, small intestine, and colon, and studies how these differences influence drug product development and disease states.
During oral drug product development, optimizing in vitro and in vivo drug release in the human gastrointestinal (GI) tract is crucial. Bile salts in the GI tract, which change under fasting and fed conditions, influence drug release, disease states, and the microbiome. Additionally, the human GI tract's microbiome plays a role in regulating disease conditions and drug treatments.
We have directly measured drug release in various regions of the human GI tract (stomach, duodenum, jejunum, and ileum) for immediate-release, modified-release, and locally-acting drug products. We also compared the profiles of 15 bile salts in different regions of the human small intestine under fasting and fed conditions. Lastly, we examined the distinct microbiome profiles in different regions of the human small intestine and colon.
Spatial and Temporal Analysis of the Stomach and Small-Intestinal Microbiota in Fasted Healthy Humans. Seekatz AM, Schnizlein MK, Koenigsknecht MJ, Baker JR, Hasler WL, Bleske BE, Young VB, Sun D. mSphere. 2019 Mar 13;4(2):e00126-19.
In Vivo Dissolution and Systemic Absorption of Immediate Release Ibuprofen in Human Gastrointestinal Tract under Fed and Fasted Conditions. Koenigsknecht MJ, Baker JR, Wen B, Frances A, Zhang H, Yu A, Zhao T, Tsume Y, Pai MP, Bleske BE, Zhang X, Lionberger R, Lee A, Amidon GL, Hasler WL, Sun D. Mol Pharm. 2017 Dec 4;14(12):4295-4304.
Measurement of in vivo Gastrointestinal Release and Dissolution of Three Locally Acting Mesalamine Formulations in Regions of the Human Gastrointestinal Tract. Yu A, Baker JR, Fioritto AF, Wang Y, Luo R, Li S, Wen B, Bly M, Tsume Y, Koenigsknecht MJ, Zhang X, Lionberger R, Amidon GL, Hasler WL, Sun D. Mol Pharm. 2017 Feb 6;14(2):345-358.
