Development Of Medical Research Research Articles

Changes in the epidemiology and clinical characteristics of viral gastroenteritis among hospitalized children in the Mainland of China: a retrospective study from 2016 to 2020

BackgroundAcute gastroenteritis (AGE) causes significant morbidity in children worldwide; however, the disease burden of children hospitalized with viral gastroenteritis in China has been rarely described. Through this study, we analyzed the data of hospitalized children with viral gastroenteritis to explore the changes in the epidemiology and clinical characteristics of viral gastroenteritis in the mainland of China.MethodsData were extracted from Futang Children's Medical Development Research Center (FRCPD), between 2016 and 2020, across 27 hospitals in 7 regions. The demographics, geographic distribution, pathogenic examination results, complications, hospital admission date, length of hospital stays, hospitalization charges and outcomes were collected and analyzed.ResultsViral etiological agents included rotavirus (RV), adenovirus (ADV), norovirus (NV) and coxsackievirus (CV) that were detected in 25,274 (89.6%), 1,047 (3.7%), 441 (1.5%) and 83 (0.3%) cases. There was a higher prevalence of RV and NV infection among children younger than 3 years of age. RV and NV had the highest detection rates in winter, while ADV in summer. Children with viral gastroenteritis were often accompanied by other diseases, such as myocardial diseases (10.98–31.04%), upper respiratory tract diseases (1.20–20.15%), and seizures (2.41–14.51%). Among those cases, the co-infection rate with other pathogens was 6.28%, with Mycoplasma pneumoniae (M. pneumoniae), Epstein-Barr virus (EBV), and influenza virus (FLU) being the most common pathogens. The median length of stay was 5 days, and the median cost of hospitalization corresponded to587 US dollars.ConclusionsThis finding suggests that viral gastroenteritis, especially those caused by RV, is a prevalent illness among younger children. Co-infections and the presence of other diseases are common. The seasonality and regional variation of viral etiological agents highlight the need for targeted prevention and control measures. Although viral gastroenteritis rarely leads to death, it also results in a significant economic burden on healthcare systems.

Mutual-DTI: A mutual interaction feature-based neural network for drug-target protein interaction prediction.

The prediction of drug-target protein interaction (DTI) is a crucial task in the development of new drugs in modern medicine. Accurately identifying DTI through computer simulations can significantly reduce development time and costs. In recent years, many sequence-based DTI prediction methods have been proposed, and introducing attention mechanisms has improved their forecasting performance. However, these methods have some shortcomings. For example, inappropriate dataset partitioning during data preprocessing can lead to overly optimistic prediction results. Additionally, only single non-covalent intermolecular interactions are considered in the DTI simulation, ignoring the complex interactions between their internal atoms and amino acids. In this paper, we propose a network model called Mutual-DTI that predicts DTI based on the interaction properties of sequences and a Transformer model. We use multi-head attention to extract the long-distance interdependent features of the sequence and introduce a module to extract the sequence's mutual interaction features in mining complex reaction processes of atoms and amino acids. We evaluate the experiments on two benchmark datasets, and the results show that Mutual-DTI outperforms the latest baseline significantly. In addition, we conduct ablation experiments on a label-inversion dataset that is split more rigorously. The results show that there is a significant improvement in the evaluation metrics after introducing the extracted sequence interaction feature module. This suggests that Mutual-DTI may contribute to modern medical drug development research. The experimental results show the effectiveness of our approach. The code for Mutual-DTI can be downloaded from https://github.com/a610lab/Mutual-DTI.

Recommendations related to the analytical equivalence assessment of gene panel testing.

Advances in cancer genome care over the past few years have included the development of gene panel testing for various biomarkers. This article summarizes issues and provides recommendations related to analytical performance evaluations for new oncology gene panels. The scope of these recommendations includes comprehensive genomic profiling assays related to gene panel testing that uses histological or serum specimens to detect gene mutations. As a research project of the Japan Agency for Medical Research and Development Research on Regulatory Science of Pharmaceuticals and Medical Devices, we convened the working group committee that consisted of more than 30 experts from academia, industry, and government. We have discussed the points that should be considered to allow maximal simplification of assessments using clinical specimens in evaluating accuracy and limit of detection in equivalence and analytical performance for 3 years. We provide recommendations specific to each type of gene mutation as well as to reference standards or specimens used for evaluations. In addition, in order to facilitate the discussion on the analytical performance of gene panel tests by multidisciplinary tumor boards of hospitals, the present recommendations also describe the items that companies are expected to provide information on in their packaging inserts and reports, and the items that are expected to be discussed by multidisciplinary tumor boards. Our working group document will be important for participants in multidisciplinary tumor boards, including medical oncologists and genome scientists, and developers of gene panels not only in Japan but also in other countries.

Points to Consider for Continuous Manufacturing of Biotechnological Drug Products

Continuous Manufacturing is a manufacturing method in which raw materials enter the manufacturing process continuously, and products are discharged continuously throughout the duration of the process including multiple unit operations. Continuous Manufacturing includes various options: Those with all stages of processing from charging raw materials to discharging final products that are continuous, and those with only certain parts of the manufacturing process that are continuous. It can be introduced in an appropriate range in consideration of the characteristics of products, manufacturing processes, robustness of processes, etc. Continuous Manufacturing is expected to have the following advantages: A wide range of manufacturing scales are available by adjusting the continuous operation time of the process; it is possible to use the same manufacturing equipment from the development stage to commercial production, eliminating the need to change to large scale manufacturing equipment; and it is possible to reduce the equipment installation area (footprint). While Continuous Manufacturing can be a major manufacturing technique of the pharmaceutical industry in the future, official documents such as guidelines for Continuous Manufacturing are limited. In particular, no official documents such as guidelines specialized in manufacturing of biotechnological drug products have been issued yet. In Japan Agency for Medical Research and Development (AMED) research project, we summarized the key points to consider for investigation of the control strategy for Continuous Manufacturing of biotechnological products as a document. In this paper, we introduce the document.

Importance of knowledge and experience in regulatory affairs for promoting pharmaceutical drug and medical device development research: a physician’s point-of-view commentary

Importance of knowledge and experience in regulatory affairs for promoting pharmaceutical drug and medical device development research: a physician’s point-of-view commentary

Targeting white matter neuroprotection as a relapse prevention strategy for treatment of cocaine use disorder: Design of a mechanism-focused randomized clinical trial

Cocaine use continues to be a significant public health problem with limited treatment options and no approved pharmacotherapies. Cognitive-behavioral therapy (CBT) remains the mainstay treatment for preventing relapse, however, people with chronic cocaine use display cognitive impairments that are associated with poor response to CBT. Emerging evidence in animal and human studies suggests that the peroxisome proliferator-activated receptor-gamma (PPAR- γ) agonist, pioglitazone, improves white matter integrity that is essential for cognitive function. This project will determine whether adjunctive use of pioglitazone enhances the effect of CBT in preventing relapse during the early phase of recovery from cocaine use disorder. This paper describes the design of a mechanism-focused phase 2 randomized clinical trial that aims first to evaluate the effects of pioglitazone on targeted mechanisms related to white matter integrity, cognitive function, and cocaine craving; and second, to evaluate the extent to which improvements on target mechanisms predict CBT response. Positive results will support pioglitazone as a potential cognitive enhancing agent to advance to later stage medication development research.

Designing medical artificial intelligence for in- and out-groups

Medical artificial intelligence (AI) is expected to deliver worldwide access to healthcare. Through three experimental studies with Chinese and American participants, we tested how the design of medical AI varies between in- and out-groups. Participants adopted the role of a medical AI designer and decided how to develop medical AI for in- or out-groups based on their experimental condition. Studies 1 (pre-registered: N = 191) revealed that Chinese participants were less likely to adopt human doctors' assistance in medical AI system when targeting patients from US (i.e., out-groups) than for patients from China (i.e., in-groups). Study 2 (N = 190) revealed that US participants were less likely to adopt human doctors' assistance in medical AI system when targeting patients from China (i.e., out-groups) than for patients from US (i.e., in-groups). Study 3 revealed that Chinese medical students (N = 160) selected a smaller training database for AI when diagnosing diabetic retinopathy among US patients (i.e., out-groups) than for Chinese patients (i.e., in-groups), and this effect was stronger among medical students from higher (vs. lower) socioeconomic backgrounds. This AI design inequity was mediated by individuals’ underestimation of out-group heterogeneity. Overall, our evidence suggests that out-group stereotype shapes the design of medical AI, unwittingly undermining healthcare quality. The current findings underline the need for more robust data on medical AI development and intervention research addressing healthcare inequity.

The correlation between prelabour rupture of the membranes and neonatal infectious diseases, and the evaluation of guideline implementation in China: a multi-centre prospective cohort study

BackgroundThe aim of this study was to describe the epidemiology of prelabour rupture of membranes (PROM) in China and to assess the association between clinical practice following the guidelines and early neonatal infections. MethodsWe conducted a prospective cohort study of 15926 deliveries in ShenZhen Baoan Women's and Children's Hospital, Xibei Women's and Children's Hospital and Chengdu Women's and Children's Hospital between August 1, 2017, to March 31, 2018. Clinical data were collected for each participant. The epidemiology of PROM was described. The association between PROM with early neonatal infectious outcomes and the influence of the implementation of the guideline on early neonatal infectious outcomes were assessed. FindingsThe incidence of PROM was 18•7%. PROM was showed to be a risk factor for neonatal infectious diseases (adjusted OR 1•92, 95%CI 1•49~2•49, p<0•0001), early-onset pneumonia (EOP) (adjusted OR 1•81, 95%CI 1•29~2•53, p=0•0006) and early-onset sepsis(EOS) (adjusted OR 14•56, 95%CI 1•90~111•67, p=0•01) for term neonates. For term neonates born from mother with PROM, induction of labor according to the guideline was a protective factor for neonatal diseases(adjusted OR 0•50, 95%CI 0•25~1•00, p=0•00498) and EOP(adjusted OR 0•32, 95%CI 0•11~0•91, p=0•03). For preterm neonates born from mother with PROM, using antibiotics according to the guideline showed to be protective for neonatal infectious diseases (adjusted OR 0•14, 95%CI 0•09~0•23, p<0•0001) and EOP (adjusted OR 0•08, 95%CI 0•04~0•14, p<0•0001). InterpretationOur study showed the risk of PROM for infectious diseases (including EOP and EOS) and the benefit of the usage of antibiotics according to the guideline for infectious diseases and EOP for preterm neonates. FundingNational Natural Science Foundation of China, Capital Medical Development Research Fund of Beijing.

CIR-Net: Automatic Classification of Human Chromosome Based on Inception-ResNet Architecture.

In medicine, karyotyping chromosomes is important for medical diagnostics, drug development, and biomedical research. Unfortunately, chromosome karyotyping is usually done by skilled cytologists manually, which requires experience, domain expertise, and considerable manual efforts. Therefore, automating the karyotyping process is a significant and meaningful task. This paper focuses on chromosome classification because it is critical for chromosome karyotyping. In recent years, deep learning-based methods are the most promising methods for solving the tasks of chromosome classification. Although the deep learning-based Inception architecture has yielded state-of-the-art performance in the 2015 ILSVRC challenge, it has not been used in chromosome classification tasks so far. Therefore, we develop an automatic chromosome classification approach named CIR-Net based on Inception-ResNet which is an optimized version of Inception. However, the classification performance of origin Inception-ResNet on the insufficient chromosome dataset still has a lot of capacity for improvement. Further, we propose a simple but effective augmentation method called CDA for improving the performance of CIR-Net. The experimental results show that our proposed method achieves 95.98 percent classification accuracy on the clinical G-band chromosome dataset whose training dataset is insufficient. Moreover, the proposed augmentation method CDA improves more than 8.5 percent (from 87.46 to 95.98 percent) classification accuracy comparing to other methods. In this paper, the experimental results demonstrate that our proposed method is recent the most effective solution for solving clinical chromosome classification problems in chromosome auto-karyotyping on the condition of the insufficient training dataset. Code and Dataset are available at https://github.com/CloudDataLab/CIR-Net.

Functional Clustering Analysis Identifies Aldehyde Dehydrogenase Phenotypes Associated with Tumor Immunity

Background: Discovering the biological functions of Aldehyde Dehydrogenases (ALDH) is the hot topic in current cancer researches. Despite the large amount of relative research results, the clinical translational research of these results was difficult to achieve. One of the most important reasons was lack of systematic understanding of ALDHs. Methods: Based on transcriptome data from 999 glioma patients, functional clustering analysis was performed to reveal the functional phenotypes of ALDH isoforms. Subsequently, ALDH subgroups closely related to gliomas were identified by expression and COX survival analysis. Finally, Gene Set Variation Analysis and pearson correlation analysis were used to exploring the biological functions of ALDHs. Findings: The present study found that ALDHs could be classified into five subgroups based on their biological functions in glioma. Three groups were closely related to malignant progression and the prognosis of gliomas and ALDHs in these groups were closely related to gene mutations, which most likely caused by changes in DNA repair functions. Further studies revealed that ALDHs play their roles by affecting tumor immune functions. The effectiveness of immune checkpoints inhibitors in treating glioma might be improved by altering the expression of ALDHs in certain subgroups. Interpretation: Our data not only comprehensively revealed the biological functions of ALDHs in glioma, but also provided a way for the potential clinical application of ALDHs targeted therapy. Funding: The National Natural Science Foundation of China; The National Key Research and Development Plan; Capital Medical Development Research Fund; Beijing Municipal Administration of Hospitals Clinical Medicine Development of Special. Declaration of Interest: The authors declare no conflict of interest. Ethical Approval: This study was approved by the Beijing Tiantan Hospital institutional review board (IRB).

Comprehensive Analysis of Immunity to Pituitary Adenomas: Implications of Immunotherapeutic Approaches for Pituitary Adenomas

Background: Immunotherapy is a promising therapeutic approach for cancers. However, the immune background and the interactions between pituitary adenomas (PAs) and the host immune system remain unclear. Methods: Poly-A enriched RNA sequencing was performed on 115 snap frozen PA samples. Estimating the Proportion of Immune and Cancer cells (EPIC) was used to detect all the main cell types (B cells, CD8+ T cells, CD4+ T cells, macrophages and NK cells) in a tumor sample from the expression of genes. Immunohistochemical (IHC) staining was used to validate the main findings. Findings: In RNA sequencing data, PA samples showed immune infiltration, including B cells, CD8+ T cells, CD4+ T cells, macrophages and NK cells. The results were further validated by IHC. Meanwhile, pathway analysis showed that TNFR superfamily (TNFRSF), IL-10 family and TGF beta (TGFβ) family were the potential mechanisms of immune infiltration in PAs. In order to search how tumor making progression with high infiltration of immune cells, gene-expression data revealed that tumor progression was related to increased expression of PD-1/PD-L1 and was associated with higher infiltration of CD8+ T cells. Besides, pathway enrichment analysis showed that regulation of death/apoptosis processes and the JAK-STAT pathway were found to be significantly enriched in samples with higher immune infiltration. At last, analysis of cancer-testis antigens (CTAs) expression in CD8+ T cells suggested that CTAG2 and TSPYL6 were potential immunotherapeutic targets in GH and non-functioning PAs, respectively. Interpretation: Our work provides new angles for understanding tumor-infiltrating immune cells. The results may inform effective checkpoint blockade and cancer vaccine therapies and make it possible to take immunotherapy into invasive functioning PAs. Funding Statement: This work was supported by the National Natural Science Foundation of China under Grant number 81471229; Capital Medical Development Research Foundation under Grant number 201811071. Declaration of Interests: No potential conflicts of interest are declared. Ethics Approval Statement: The PA tissue collection was approved by the Institutional Review Board of Beijing Tiantan Hospital, Capital Medical University. All procedures involving human participants conformed to the ethical standards of the national research committee and the 2013 Helsinki Declaration, which were approved by the Institutional Review Board of Beijing Tiantan Hospital, Capital Medical University. Informed consent was obtained from all patients prior to their enrollments in this study.

Statistical survey of open source medical image databases on the Internet

Background and Objectives: Nowadays, more and more open source medical imaging databases are published on the Internet for medical teaching, algorithm development, and medical research. However, a statistical survey of these databases is still lacking. In this survey, we summarize the current status of open source medical image databases on the Internet. The aim is to make it easier for everyone to find and use open source medical image data. Methods: Information about publicly available medical image databases was collected by searching for scientific papers and Internet search engines. Based on the collected information, the number of databases and the number of images were counted for different diseases, body parts, imaging modalities, and countries. Results: Cancer, particularly breast cancer and lung cancer, ranked top in database numbers among all diseases. The breast, brain, lung, and chest are the top four body parts in terms of database numbers. Computed tomography, magnetic resonance imaging, and X-ray are the most common imaging modalities in the open source datasets. The USA and the Netherlands are the top two countries who own the most databases. Conclusions: The rankings for diseases and body parts were closely related to the diseases morbidity and the health-care expenditure of a country. The number of open sources of medical imaging databases is still growing; there is a need for continuous statistical research on their existence status in the coming years. The list of all the collected databases is opened on the Internet (https://docs.qq.com/sheet/DQWF0QlZKVHpHU1Za).

Mobile alcohol biosensors and pharmacotherapy development research.

Recent advances in biosensor technology herald a major shift in the way alcohol use will be tracked in humans. Wearable biosensors can passively and continuously monitor wearers' alcohol consumption in real time. An important application of these biosensors is to improve the way medication for alcohol use disorder (AUD) is tested in clinical research. Both laboratory-based screening paradigms and clinical trials have methodological problems that impact their efficiency and predictive validity. Medication screening using laboratory-based methods is a resource-intensive assessment of a single episode of behavior in a non-representative setting. Clinical trials rely on participant self-report to document medication-induced changes in drinking behavior. This review describes how mobile biosensors can be leveraged to improve AUD medication development research. We first review the current state of alcohol biosensor technology with a focus on strengths and limitations of the devices. We describe how multiple biosensors can be combined to create a far more detailed record of drinking compared to single biosensor platforms. We then discuss each phase of the medication development pipeline in turn (i.e., phases 1-4) and describe how mobile biosensors can be incorporated in standard medication testing paradigms to improve efficiency and predictive validity. We conclude with discussion of challenges associated with using currently available biosensors for medication testing and recommendations for researchers wishing to incorporate alcohol biosensors into their own research.

WS10-2 - Approaches to cancer treatment in the elderly: Gastric cancer

A standard form of chemotherapy for elderly patients with gastric cancer has yet to be established. The factors for this can be grouped into 3 categories: (1) elderly subjects have been excluded from major phase III trials in Japan, (2) there are few clinical studies targeting only for the elderly, and randomized trials have not conducted only for the elderly, and (3) the elderly are a diverse population, so using a uniform therapy to treat the elderly as a whole is not feasible. Over the past few years, the concept of assessing the diversity of elderly patients beforehand and then selecting an appropriate treatment has gained ground, but there is insufficient evidence substantiating the validity of that concept. In the area of gastric cancer, a randomized trial focusing on a form of geriatric assessment is underway to deal with the 3 categories of factors mentioned earlier. S-1 therapy is readily used to treat cancer in elderly patients, but SOX (S-1+L-OHP) therapy would presumably have greater efficacy than therapy with S-1 alone. Thus, the primary objective of the current trial was to compare S-1 monotherapy and SOX (S-1+L-OHP) therapy using the the G8 and the Charlson Comorbidity Index for geriatric assessment. The secondary objective of this trial was to create a dataset of elderly patients with gastric cancer undergoing chemotherapy along with accompanying prospective clinical information and geriatric assessments. A potential secondary use of this dataset would be to establish an adverse event scoring system. This trial is being conducted by a Japan Agency for Medical Research and Development (AMED) research group with public funding. This presentation at this workshop will describe approaches that have been taken in the area of gastric cancer before the aforementioned trial was devised.

Emerging Pharmacologic Treatments for Adolescent Substance Use: Challenges and New Directions.

Adolescence is a key period in the development of substance use and misuse. Substance use typically begins during adolescence and prevalence rates for many substance use disorders peak before age 21 years. Yet, despite clinical demand, treatments for youth rely almost entirely on psychosocial interventions that yield only modest benefit. One potential way to improve treatment effects is to augment the best available psychosocial interventions with pharmacotherapy. Although pharmacotherapy research has advanced care for adults with substance use disorders, no medication is indicated for adolescents and controlled trials with teenagers are scant. Optimizing treatments for youth will require closing this important gap in medication development research. In this paper we review the paucity of pharmacotherapy research for adolescent substance misuse, and we discuss how we can leverage human laboratory paradigms and technology to advance our understanding regarding if and how medications may improve treatment options for youths.

Topiramate and motivational enhancement therapy for cannabis use among youth: a randomized placebo-controlled pilot study.

Cannabis misuse accounts for nearly all of the substance abuse treatment admissions among youth in the United States. Most youth do not experience sustained benefit from existing psychosocial treatments; however, medication development research for treating adolescent cannabis misuse is almost nonexistent. We conducted a double-blind, placebo-controlled, pilot study to test the potential efficacy of topiramate plus motivational enhancement therapy (MET) for treating cannabis use among adolescents. Sixty-six heavy cannabis users, ages 15 to 24 years, were randomized to one of two 6-week treatment conditions: topiramate plus MET or placebo plus MET. Topiramate was titrated over 4 weeks then stabilized at 200 mg/day for 2 weeks. MET was delivered biweekly for a total of three sessions. Only 48 percent of youths randomized to topiramate completed the 6-week trial (n = 19), compared with 77 percent of youths in the placebo condition (n = 20). Adverse medication side effects were the most common reason for withdrawal among participants in the topiramate group. Latent growth models showed that topiramate was superior to placebo for reducing the number of grams smoked per use day, but it did not improve abstinence rates. The same pattern of results was found when values for missing outcomes were imputed. We show that topiramate combined with MET demonstrated efficacy for reducing how much cannabis adolescents smoked when they used but did not affect abstinence rates. The magnitude of this effect was modest, however, and topiramate was poorly tolerated by youths, which calls into question the clinical importance of these findings.

Recent Advance in Applications of Proteomics Technologies on Traditional Chinese Medicine Research.

Proteomics technology, a major component of system biology, has gained comprehensive attention in the area of medical diagnosis, drug development, and mechanism research. On the holistic and systemic theory, proteomics has a convergence with traditional Chinese medicine (TCM). In this review, we discussed the applications of proteomic technologies in diseases-TCM syndrome combination researches. We also introduced the proteomic studies on the in vivo and in vitro effects and underlying mechanisms of TCM treatments using Chinese herbal medicine (CHM), Chinese herbal formula (CHF), and acupuncture. Furthermore, the combined studies of proteomics with other “-omics” technologies in TCM were also discussed. In summary, this report presents an overview of the recent advances in the application of proteomic technologies in TCM studies and sheds a light on the future global and further research on TCM.

Investigation of the project leaders' cognition to Capital Medical Development Research Foundation

Objective To investigate the cognition of persons who lead the programmes of Capital Medical Development Research Foundation (referred to Capital Fund).Method We formed electronic questionnaires mainly by the Expert Meeting Law,and investigated the cognition of the project leader of Capital Fund,relying on the special work notice of Beijing Municipal Health Bureau.We evaluated reliability by Cronbach's alpha coefficient,evaluated validity by content validity,and analyzed the project leader's cognition of the function,satisfaction,purpose and influence of Capital Fund.Result The satisfaction index with method of the foundation's management and the cognition index to the foundation are both over 95％,the objective and the impact of Capital Fund are popular,showing that the Capital Fund promoted the development of medicine.Conclusion The project leader of Capital Fund have positive cognition and satisfaction,and also showed their expectation to the foundation. Key words: Capital medical development research foundation; Project leader; Cognition

Designing, prototyping and manufacturing medical devices: an overview

Nowadays medical devices are a fast-growing industry. Advances in design, materials and technologies have increased the potential to find better solutions for those medical problems whose remedies were, up until now, unimaginable. A broad spectrum of new solutions is available ranging from new materials to new products, tools and procedures. Medical doctors have discovered how the latest advances in engineering support their work by making surgery or treatment processes easier than ever before. For this reason, medical devices are now a hot topic of industrial and academic interest in fields such as design, prototypes or manufacturing. This paper introduces a special issue with several medical device case studies, illustrating new developments in product design, material selection and prototype methods. In addition, the paper also reviews medical device development research and depicts some case studies to better explain the relationship between technology/engineering and medical devices. The paper contributes with some data on this combination of research fields.

Drug development and research in New Zealand: policies affecting the industry

AbstractMany countries employ a range of policies to support their drug development industry. The support is primarily because of the perceived potential benefits from wealth creation, employment, and international trade related to a high‐technology industry. New Zealand (NZ) has a growing drug development industry; this article reports on the results of interviews with people representing the industry. The NZ industry reported that government policies that included funding of scientific, medical, and drug development research, a robust regulatory system, and strong patent laws have created a cluster of expertise for specialized drug development services. This is similar to those that have been reported to encourage the biotechnology industries of many countries. Threats to the industry in NZ include insufficient funding, small industry size, insufficient supportive policies, and stakeholders' lack of understanding of the industry. These barriers differ from those of developing countries such as China and India, probably because NZ's industry is built on its scientific and medical research rather than its manufacturing capability. The specific policies requested to further support the NZ industry include increased government investment, improved management of funding, and support for research, education, and career development. Drug Dev Res 73: 1–10, 2012. © 2011 Wiley Periodicals, Inc.