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Indiana University-Purdue University Indianapolis (IUPUI) / The DNA Base Excision Repair (BER) pathway repairs DNA damaged by endogenous and exogenous agents including chemotherapeutic agents. Removal of the damaged base by a DNA glycosylase creates an apurinic / apyrimidinic (AP) site. AP endonuclease1 (Ape1), a critical component in this pathway, hydrolyzes the phosphodiester backbone 5’ to the AP site to facilitate repair. Additionally, Ape1 also functions as a redox factor, known as Ref-1, to reduce and activate key transcription factors such as AP-1 (Fos/Jun), p53, HIF-1α and others. Elevated Ape1 levels in cancers are indicators of poor prognosis and chemotherapeutic resistance, and removal of Ape1 via methodology such as siRNA sensitizes cancer cell lines to chemotherapeutic agents. However, since Ape1 is a multifunctional protein, removing it from cells not only inhibits its DNA repair activity but also impairs its other functions. Our hypothesis is that a small molecule inhibitor of the DNA repair activity of Ape1 will help elucidate the importance (role) of its repair function in cancer progression as wells as tumor drug response and will also give us a pharmacological tool to enhance cancer cells’ sensitivity to chemotherapy. In order to discover an inhibitor of Ape1’s DNA repair function, a fluorescence-based high-throughput screening (HTS) assay was used to screen a library of drug-like compounds. Four distinct compounds (AR01, 02, 03 and 06) that inhibited Ape1’s DNA repair activity were identified. All four compounds inhibited the DNA repair activity of purified Ape1 protein and also inhibited Ape1’s activity in cellular extracts. Based on these and other in vitro studies, AR03 was utilized in cell culture-based assays to test our hypothesis that inhibition of the DNA repair activity of Ape1 would sensitize cancer cells to chemotherapeutic agents. The SF767 glioblastoma cell line was used in our assays as the chemotherapeutic agents used to treat gliobastomas induce lesions repaired by the BER pathway. AR03 is cytotoxic to SF767 glioblastoma cancer cells as a single agent and enhances the cytotoxicity of alkylating agents, which is consistent with Ape1’s inability to process the AP sites generated. I have identified a compound, which inhibits Ape1’s DNA repair activity and may have the potential in improving chemotherapeutic efficacy of selected chemotherapeutic agents as well as to help us understand better the role of Ape1’s repair function as opposed to its other functions in the cell.

After numerous renewals and reignitions since the initiation of the "War on Cancer" more than five decades ago, the recent reignition of "Moonshot to Cure Cancer" points to the systemic persistence of cancer as a major cause of loss of life and livelihood. Literature points to the diminishing returns of cancer research through time, as well as heterogeneities in cancer research centers' innovation strategies. This dissertation focuses on the strategic decision by cancer research centers to invest their resources in conducting early phases of clinical trials on new candidate drugs/treatments (resembling exploration) or late phases of clinical trials that push established candidates towards acquiring FDA approvals (resembling exploitation). The extensive clinical trials data suggests that cancer research centers are not only different in their emphasis on exploratory trials, but also in how their emphasis is changing over time. This research studies the dynamics of this heterogeneity in cancer research centers' innovation strategies, how experiential learning and capability development interact to cause dynamics of divergence among learning agents, and how the heterogeneity among cancer research centers' innovation strategies is affected by the dynamics of learning from experience and capability development. The findings of this dissertation shows that endogenous heterogeneities can arise from the process of learning from experience and accumulation of capabilities. It is also shown that depending on the sensitivity of the outcome of decisions to the accumulated capabilities, such endogenous heterogeneities can be value-creating and thus, justified. Empirical analysis of cancer clinical trials data shows that cancer research centers learn from success and failure of their previous trials to adopt more/less explorative tendencies. It also demonstrates that cancer research centers with a history of preferring exploratory or FDA trials have the tendency to increase their preference and become more specialized in one specific type (endogenous specialization). These behavioral aspects of the cancer research centers' innovation strategies provide some of the tools necessary to model the behavior of the cancer research efforts from a holistic viewpoint. / Doctor of Philosophy / The "Moonshot to Cure Cancer" was renewed most recently in September 2022. However, renewal and reignition of this national collective effort is nothing new; this effort started as "War on Cancer" in 1971 and has been reignited numerous times. After more than 50 years of our collective battle to cure cancer, it claims almost 600,000 lives annually and remains as the second leading cause of death in the US. There are a wide variety of cancer research centers from all around the world contributing to this collective effort and they make considerably different decisions regarding their investment in research. There is evidence suggesting that some of the research centers' investment decisions are not optimal and can be improved. It has been shown that systems such as patent regulations can be revised to encourage such improved decisions among cancer research centers. This dissertation focuses on the process of clinical trials for new drugs/treatments for cancer. New drugs/treatments have to pass different phases of trials to ensure that they are safe and effective before they can acquire FDA approvals. Cancer research centers decide whether to invest in early phases of clinical trials for new drug/treatment candidates or invest in late phases of trials for candidates that have already passed the early phases. The clinical trials data show that there has been a sharp rise in number of early phases of trials on new drugs/treatments; however, the same rise cannot be seen in the late phases of trials resulting in approvals. It can also be seen that different research centers put different levels of emphasis on initiating early phases of trials for new drugs/treatments (exploration). In this dissertation, the hypothesis is that this ongoing dilemma that cancer research centers face to invest on how much emphasis to put on exploration in their clinical trials is affected by learning from experience. To test this hypothesis, a mathematical model is used to show differences in decisions can be causes solely by learning from experience, when the decision maker is learning "what to do" from success/failure of previous efforts and learning "how to do it" from practicing and accumulating the required skills. Then, the hypothesis is formally tested using the clinical trials data. The results show that cancer research centers learn from the success and failure of their previous exploratory trials when deciding on their emphasis on exploration. Also, they accumulate skills, resources, and capabilities relevant to the type of research the conduct more often and specialize in either of late- or early-phases of trials. The findings of this dissertation show that learning from experience can cause in differences in decisions. It also finds evidence that cancer research centers learn to place different levels of emphasis on exploration in their clinical trials. These findings can later be used in models of the cancer research ecosystem to study how funding structures and policies can be changed to improve the outcomes of our collective effort to cure cancer.

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No description available.

Allostery is a regulatory process whereby a perturbation by an effector at one discrete locus creates a conformational change that stimulates a functional change at another. The two sites communicate through networks of interacting residues that respond in a concerted manner to the allosteric perturbation. These allosteric networks are traditionally mapped with high resolution structure determination techniques to understand the conformational changes that regulate protein function as well as its modulation by allosteric ligands and its dysfunction caused by disease-related mutations (DRMs). However, high resolution structural determination techniques, such as X-ray crystallography, cryo-electron microscopy and nuclear Overhauser effect NMR spectroscopy are not always amenable for systems plagued by poor solubility and line broadening caused by μs-ms dynamics or systems where allostery relies primarily on dynamical rather than structural changes. This dissertation discusses methodologies to map the allosteric sites and pathways for such challenging systems. The foundation of this approach is to model allosteric pathways in the context of their respective thermodynamic cycles. In chapter 2, the thermodynamic cycle of a DRM in the hyperpolarization-activated cyclic nucleotide-gated ion channel 4 (HCN4) is analyzed with respect to structure, dynamics and kinetics, revealing how the DRM remodels the free energy landscape of HCN4 and results in a loss-of-function disease phenotype. In chapter 3, the mechanism of action of an uncompetitive inhibitor for the exchange protein activated by cAMP is elucidated by characterizing its selectivity for distinct conformations within the thermodynamic cycle that are trapped using a combination of mutations and ligand analogs. In chapter 4, we discuss two new protocols for the chemical shift covariance analysis (CHESCA). The CHESCA is an approach that identifies allosteric signaling pathways by measuring concerted residue responses to a library of chemical perturbations that stabilize conformational equilibria at different positions. Overall, the approaches discussed in this dissertation are widely applicable for mapping the mechanisms of allosteric perturbations that arise from ligand binding, post-translational modifications and mutations, even in systems where traditional structure determination techniques remain challenging to implement. / Thesis / Doctor of Philosophy (PhD) / Allostery is a regulatory mechanism for proteins, which controls functional properties of one distinct site through the perturbation of another distinct, and often distant, site. The two sites are connected via a series of residues that undergo conformational changes once perturbed by the allosteric effector. Mapping these communication pathways reveals mechanisms of protein regulation, which are invaluable for developing pharmacological modulators to target these pathways or for understanding the mechanisms of disease mutations that disrupt these pathways. Allosteric pathways have been traditionally determined using structure determination approaches that provide a static snapshot of the protein’s structure. However, these approaches are typically not effective when allostery relies extensive changes in dynamics. The goal of this thesis was to develop methods to characterize systems that are dynamic or otherwise unsuitable for traditional structure determination. Herein, we utilize NMR spectroscopy to analyze the allosteric mechanisms of three cAMP-binding proteins involved in cardiovascular health.

Indiana University-Purdue University Indianapolis (IUPUI) / Model-based drug development has become an essential element to potentially make drug development more productive by assessing the data using mathematical and statistical approaches to construct and utilize models to increase the understanding of the drug and disease. The modeling and simulation approach not only quantifies the exposure-response relationship, and the level of variability, but also identifies the potential contributors to the variability. I hypothesized that the modeling and simulation approach can: 1) leverage our understanding of pharmacokinetic-pharmacodynamic (PK-PD) relationship from pre-clinical system to human; 2) quantitatively capture the drug impact on patients; 3) evaluate clinical trial designs; and 4) identify potential contributors to drug toxicity and efficacy. The major findings for these studies included: 1) a translational PK modeling approach that predicted clozapine and norclozapine central nervous system exposures in humans relating these exposures to receptor binding kinetics at multiple receptors; 2) a population pharmacokinetic analysis of a study of sertraline in depressed elderly patients with Alzheimer’s disease that identified site specific differences in drug exposure contributing to the overall variability in sertraline exposure; 3) the utility of a longitudinal tumor dynamic model developed by the Food and Drug Administration for predicting survival in non-small cell lung cancer patients, including an exploration of the limitations of this approach; 4) a Monte Carlo clinical trial simulation approach that was used to evaluate a pre-defined oncology trial with a sparse drug concentration sampling schedule with the aim to quantify how well individual drug exposures, random variability, and the food effects of abiraterone and nilotinib were determined under these conditions; 5) a time to event analysis that facilitated the identification of candidate genes including polymorphisms associated with vincristine-induced neuropathy from several association analyses in childhood acute lymphoblastic leukemia (ALL) patients; and 6) a LASSO penalized regression model that predicted vincristine-induced neuropathy and relapse in ALL patients and provided the basis for a risk assessment of the population. Overall, results from this dissertation provide an improved understanding of treatment effect in patients with an assessment of PK/PD combined and with a risk evaluation of drug toxicity and efficacy.

在學術領域之中，其過去對於新藥產業的研究大多集中於「新藥發展策略」、「產業環境分析」與「智慧財產權策略」等領域，而探討新藥研發各階段之團隊組成與運作模式的研究仍然極少。 本研究以個案訪談法為主要研究方式，深入探討兩家台灣新藥研發公司（包括基亞生技、台灣微脂體），並以『新藥研發流程』與『技術知識特質』兩個構面來探索其對於『新藥研發專案團隊運作』之影響。 所得到的初步研究發現包括： 1. 新藥研發專案各階段中，技術知識路徑相依程度與技術知識系統複雜程度呈現負相關，當路徑相依程度越高時，系統複雜程度則越低。 2. 新藥研發專案隨著階段的推進，專案團隊的組成與結構也會隨之產生變化，臨床前與臨床試驗皆有不同的團隊組成與結構。 3. 技術知識系統複雜程度會影響新藥研發團隊組成的異質/多元程度：技術知識系統複雜程度越高，其團隊組成的異質/多元程度越高。 4. 技術知識路徑相依程度會影響團隊採取何種團隊運作策略：（1）路徑相依程度愈「高」或是愈「低」，專案團隊會傾向採取「自行發展」的團隊運作模式；（2）路徑相依程度為「中」時，專案團隊會傾向採取先執行「初步研發」活動之後，再與外部廠商進行「合作研發」。 5. 技術知識路徑相依程度會影響新藥研發專案各階段的團隊類型：（1）技術知識路徑相依程度愈低，專案團隊會傾向採用「重量級」、「自主型」的團隊運作模式；（2）技術知識路徑相依程度愈高會傾向採用「功能型」、「輕量級」的團隊運作模式。 6. 技術知識內隱化程度愈高，該專案在團隊運作上愈容易將外部成員視為內部團隊，甚至在團隊組成上直接將外部成員納入內部團隊之中。 7. 在臨床試驗階段，試驗主持人的過往經驗為成功關鍵之一。 8. 新藥研發廠商若擁有先導研發的能力，可以減短研發時程與成本。 / Most of previous the studies on pharmaceutical industry have been focused on the development strategy, environmental analysis and intellectual property. Very few of them emphasize the stage of new drug development concerning the project team management. This study uses technological knowledge characteristics (path dependence, complexity, and explicitness) and drug development process (drug discovery, non-clinical, pre-clinical, and clinical ) to explore the effect upon project team management. The result of this study： 1. In every stage of new drug development, the path dependence and the complexity of technological knowledge have significantly negative correlation. 2. When the new drug development project evolves into the clinical stage, the structure of project team will be different. 3. The complexity of technological knowledge can affect the composition of team members. If the complexity of technological knowledge is higher, the complexity of members is higher. 4. The path dependence of technological knowledge can affect the development strategy. If the path dependence is higher or lower, the team members prefer “inner development”. If the path dependence is medium degree, the team members prefer “primary inner development” and then “cooperative research and development”. 5. The path dependence of technological knowledge can affect the team structure. If the path dependence is higher, the enterprise prefers “Heavyweight team structure” or “Autonomous team structure”. If the path dependence is lower, the enterprise prefers “Lightweight team structure” or “Functional team structure”. 6. If the explicitness of technological knowledge is higher, the enterprise intends to recruit team member from outside. 7. In clinical stage, the practice investigator can be key person of the success. 8. If the enterprise has the ability of “primary inner development”, the time and the cost of the new drug development can be reduced.

有鑑於生物科技成為科技趨勢，以及其創造出的龐大價值，近年來台灣也開始大力推動生技產業的發展。產業是企業的組合，企業的成長與否正是驅動產業生態變化的主要原因。本研究主要探討台灣生技藥物研發公司的創業過程，希望透過研究成果對台灣生技公司的發展有所貢獻。 　　本研究的研究架構以Timmons Model做為主軸，以機會、資源、團隊做為主要的研究構面，先對個案公司進行靜態的研究構面探討，然後分析其發展的動態平衡過程。 / Because biotechnology sets a trend and creates great value, Taiwan government tries to develop his own biotechnology industry. However, an industry will bloom if most of companies related to the industry are operated well. The objective of this study is to observe and analyze the entrepreneurial process of biomedical R&D companies in Taiwan. 　　The research bases on Timmons Model that was developed by Timmons for analyzing an entrepreneurial process of a company and consists of three driving forces, opportunity, resource, and team. Every entrepreneurial process of companies in the thesis is observed first according to the three driving forces. Then it is analyzed by using the idea of constant balancing.