11^th International Conference on Clinical Trials November 09-10, 2023 London, UK

Biography:

Tony Lockett is a researcher in rare diseases and medical ethics. He is committed to sustainability and inclusiveness in Advanced Medical Products. He is a member of the Standards Group for rare diseases, Chair of the FPM Rare Disease Expert Group and Chair of several HRA and non-HRA ethics committees. He has developed a model for standards development in Rare Disease. He is also the lead investigator on a range of drug delivery technologies suitable for AMP delivery in low-middle income companies

Abstract:

Current clinical trial regulation stipulates that for informed consent to be valid the researcher has to ensure that the participant is adequately informed and has understood the information. This is generally interpreted as a requirement that it is the duty of sponsors and investigators to ensure that participants understand the information provided. Recent research has shown that this requirement is inconsistently met. While 92% of information sheets surveyed stated that a participant would have a conversation with the participants about understanding, none of the sheets reviewed contained an objective assessment of understanding. Measures to manage the inconsistency in informed consent include. The introduction of standards into consent forms.  The HRA is implementing a standards document for informed consent, including guidance on content, readability and consultation. The introduction of decision aids into consent and the use of decision understanding tools. The adoption of ethical frameworks such as the precautionary principle into consent

However, there is a concern that the requirement for total disclosure sets too high a barrier to consent, particularly in Advanced Medicinal Products (AMP). In the early stage development of AMP investigators and sponsors may not have complete information to share. Furthermore,  the proposed changes may not solve the issues of consent; studies have shown that it is health literacy, rather than readability is one of the barriers to informed consent. An alternative proposal is the introduction of risk based consent. The idea risk-based management of clinical trials is not new, and risk-based design and monitoring of clinical trials is now commonplace. Its use in the COVID epidemic has provided a glimpse of the potential of risk-based consent, but will it solve the issue of consent – particularly AMP?

Biography:

Dr. Wenle Zhao is a professor in biostatistics at the Department of Public Health Science in the Medical University of South Carolina, USA. He has published several randomization algorithms, including the Block Urn Design as better alternative to permuted block design to enhance allocation randomness, the Minimal Sufficient Balance method as better alternative to the Minimization method to control imbalances in multiple baseline covariates, the Step-forward Randomization for emergency treatment trials, the Mass-weighted Urn Design to accurately target unequal allocations in response-adaptive trials, the Asymptotic Maximal Procedure for small trials intended to use randomization tests. These randomization designs have been implemented in many trials, including those in the Stroke Trials Network (StrokeNet) and Neurological Emergencies Treatment Trials (NETT) network, both funded by NIH

Abstract:

The superiority of maximum tolerated imbalance (MTI) randomization procedures over the traditional permuted block design has been well documented in literature. However, the permuted block design remains the most used method in clinical trial practices. This trend may reflect a lack of awareness of the disadvantages of permuted block design and a lack of easy implementation methods of MTI procedures. This presentation evaluates  the statistical properties and implementation methods for five MTI procedures (Big Stick Design, Biased Coin Design with Imbalance Tolerance, Ehrenfest Urn Design, Block Urn Design, Asymptotic Maximal Procedure) and permuted block design based on the conditional allocation probability. Analytic results for the probability of deterministic assignments, the probability of complete random assignments, the probability of correct guess, as well as the standard deviation of treatment imbalance for these randomization designs. Recommendations for the selection of proper randomization design are provided for trials with and without stratification based on the consideration of treatment allocation randomness. Furthermore, a unified framework for central real-time subject randomization is proposed for the implementation of different randomization algorithms based on their conditional allocation probability functions. This approach removes the requirement of pre-generated randomization sequences, eliminates the risk of treatment allocation concealment failures, and providers potentials for the use of hierarchy randomization using MTI procedures. Compared to stratified permuted block design, this new strategy offers more effective controls for both imbalances in multiple baseline covariates and the overall treatment imbalance. This randomization design has been implemented in more than 10 multicenter clinical trials in the NIH Stroke Trials Network

Biography:

Dr. Wenle Zhao is a professor in biostatistics at the Department of Public Health Science in the Medical University of South Carolina, USA. He has published several randomization algorithms, including the Block Urn Design as better alternative to permuted block design to enhance allocation randomness, the Minimal Sufficient Balance method as better alternative to the Minimization method to control imbalances in multiple baseline covariates, the Step-forward Randomization for emergency treatment trials, the Mass-weighted Urn Design to accurately target unequal allocations in response-adaptive trials, the Asymptotic Maximal Procedure for small trials intended to use randomization tests. These randomization designs have been implemented in many trials, including those in the Stroke Trials Network (StrokeNet) and Neurological Emergencies Treatment Trials (NETT) network, both funded by NIH

Abstract:

Abstract: Random treatment assignment provides the fundamental protection for the integrity of clinical trial results. Permuted block randomization and minimization method remain the most used randomization methods in clinical trial practice. In trials with unequal or response adaptive target allocations, multiple categorical or continuous baseline covariates, and large number of clinical sites, both stratified permuted block randomization and minimization are unable to meet the investigators’ needs.

Over the past few decades many advanced randomization methods have been published with superior statistical properties in treatment allocation imbalance control, baseline covariate balancing, and allocation randomness protection. However, these newer randomization methods have gained few applications in real trials, mainly due to implementation difficulties. Many interactive voice response system (IVRS) and interactive web response system (IWRS) packages and electronic data capture (EDC) systems like REDCap use pre-generated randomization lists, allowing stratified permuted block randomization only. Knowledge dissemination for implementing advanced randomization methods in clinical trial information systems is highly demanded.

The first part of this 90-minute education workshop reviews the statistical performances of stratified permuted randomization, minimization, as well as those newly published randomization methods, including a family of restricted randomization designs with maximum tolerated imbalance (MTI) and the minimal sufficient balance strategy. These randomization designs will be quantitatively compared based on the capacity of accurately achieving target allocation (two-arm or multi-arm equal or unequal allocations), effectively controlling imbalances in baseline covariates (few or many categorical or continuous covariates), and the allocation randomness measured by the proportion of deterministic assignments and correct guess probability.

 The second part of the workshop will discuss the implementation methods for these advanced randomization methods in the clinical trial information system, illustrated with real trial examples. The workshop will present a generic strategy to integrate the subject randomization program as a special case report form (CRF) into the trial’s EDC system in which eligibility and baseline covariates data are collected. Practical issues associated with subject randomization will be discussed, including the generation of randomization code in drug studies for treatment blinding and masking, randomization algorithm adjustment for site study drug availability, randomization algorithms for the burn-in period and fixed allocation period prior to the start of response adaptive randomization (RAR) phase, target allocation update in RAR trial with pre-specified time period length or pre-specified subject enrollment size, selection between balancing categorical covariates after dichotomizing vs. balancing continuous baseline covariates, handling of site operation errors in subject randomization, and emergency randomization in case technical glitches occur at site or the trial’s EDC system.       

Goal of Session: Attendees of this education workshop is expected to learn what are better alternatives to the stratified permuted block randomization and minimization, how to select a randomization method to better meet the requirement of their trial, how to implement the selected randomization algorithm into the EDC system, and how to deal with possible glitches in the randomization procedure.  The workshop is expected to be conducted in an interactive way. Attendees are encouraged to bring questions and cases for discussion. Knowledge and experiences in basic statistics and information system programming can help, but not required, to understand the contents of this workshop

Biography:

Stuart holds a chair in Pharmaceutical Medicine at King’s College London. He has spent the last 22 years working in translational research to develop innovative therapies. His research career started in the pharmaceutical industry working at AstraZeneca, Pfizer and then MedPharm. Almost 19 years ago he joined King’s College London. At King’s, he completed a Masters's in Academic Practice, and he combined this educational training with his research and industry experience to establish the Centre for Pharmaceutical Medicine Research, which is a global leader in research and postgraduate education in the process of development and lifecycle management of medicines. He has a strong research track record, supervising 16 postdoctoral workers, 40 PhD students, and > 100 Masters students which have generated > 80 publications and > £5 million of research income. He is a fellow of the Faculty of Pharmaceutical Medicine and the UK Association of Pharmaceutical Scientists

Abstract:

Decentralized clinical trials (DCTs) are trials "where some or all of the trial-related activities occur at locations other than traditional clinical trial sites"(1). They offer opportunities to collect relevant, real-world, real-time clinical data and to enhance clinical trial quality, recruitment and completion. However, to realize these advantages digital health technologies (DHTs), which are at the heart of DCTs, must robustly measure clinical outcomes, enable secure data transmission, and facilitate effective large data set processing.

DHT use in clinical trials has been increasing (less than 1% in 2010 to more than 10% in 2020) and this will allow refinement of their deployment and applications (2). However, whilst DHT’s are capable of real-time remote monitoring of treatment a 2021 systematic review, which reported 45 randomized and controlled DCTs, showed that of the 30 cited completed trials, none used real-time monitoring (3). Except for several pilot studies in neurology, this trend has been sustained with only a limited number of large prospective DCTs using used DHTs for real-time data monitoring (4). Experience has therefore shown that paper-based elements of trials can be digitized, but there are few large prospective trials that have embraced real-time data collection using digital devices.

Although commercial data collection devices are being evaluated for use in DCTs, they were not designed for this purpose and are available for a limited number of clinical outcome measurements (5). Given the potential rewards of wider DCT implementation, now is the time to invest both effort and money into engineering the necessary new data collection, transfer and analysis tools. We call on clinicians, patients and trial managers to work with engineers and analysts to produce a new generation of data collection devices and data analysis tools that function effectively in real-world environments and meet the needs of the global regulatory frameworks for evaluation of new medical interventions.   

Biography:

Graham McClelland is a Professor of Pharmaceutical Medicine at King’s College London. He is a qualified biologist, psychologist and pharmacologist, and spent over 30 years working in R&D for the pharmaceutical industry. Whilst employed in the pharma, in 1999 he initiated a part-time MSc course in Clinical Pharmacology at the Postgraduate Medical School of the University of Surrey, where he was a Visiting Professor and the Course Director until 2009. In 2009 he moved to Egypt, where he formed the public company, Luxor Developments, and carried out teaching and consultancy work in the region, and in 2011 was appointed a Visiting Professor in the Faculty of Medicine of the University of Alexandria1. He returned to the UK in 2015, and shortly after, joined King’s where, he is now Course Director of the integrated MSc Apprenticeship in Clinical Pharmacology

Abstract:

Statement of the Problem: Patient engagement is increasingly being encouraged by regulatory authorities and adopted by pharmaceutical companies. However, the involvement of individual patients and/or their carers, and/or representatives from patient organisations has been inconsistent and based upon a moral view rather than objective evidence of benefit. This work here attempts to begin to build an evidence-based approach to patient engagement in medicine development. Methodology & Theoretical Orientation: Firstly, a systematic literature review was conducted to conceptualise the meaning of patient engagement, to investigate current models and frameworks, and to identify key elements by a thematic analysis. Secondly, semi-structured interviews were conducted with industry practitioners to identify potential metrics for patient engagement. Thirdly, members of the UK Association of Medical Research Charities (AMRC) were surveyed on how they provide patient opinions. Findings: The systematic literature review identified 25 relevant articles, which generated eight themes on ‘how’ to engage patients in medicine development – 1. The need for a meta framework, 2. Metrics, 3. Capacity, 4. Roles, 5. Partnership, 6. Culture change, 7. Legal agreement, 8. Digital platforms. Plus, five themes on ‘where’ to engage patients in medicine development – 1. Clinical trial design and planning, 2. Clinical trial priority setting, 3. Clinical trial conduct, 4. Communication, 5. Committee membership. Interviews with nine experienced pharmaceutical industry practitioners showed that methods for assessing the amount, quality and value of patient engagement is currently lacking. 24% of the membership of the AMRC responded to the online survey, of which 86% had experience in providing patient representation in medicine development, and used a variety of methods to provide input, but 77% had not received any training on patient engagement. Conclusion & Significance: As patient engagement becomes increasingly common, there remains a need for more scientific evidence, metrics and education.

Biography:

Dr. Mohammad Nadeem Khan is a Senior Research Associate at SAMC&; PGI, SAU, and INDORE (INDIA). He post graduated from Jiwaji University Gwalior, INDIA. He done Ph.D. in Biotechnology from BU, BHOPAL, INDIA in 2014.Since 2013 he was worked as Academicians in various University. He has published more than 40 research paper in reputed national international journal and 3 book and 6 book chapter. He serve position of Editor and Reviewer of various National and International pioneer research journal. He is currently serving Clinical Research and Trails Co-ordinator of department of clinical pharmacology, SAMC& ;PGI, Indore and doing Phase-1 to Phase-4 clinical research and trials. He is major research interest in Biopharmaceuticals and In-Silico research, molecular research and pathophysiology of various diseases model

Abstract:

Meeting the objectives of investigations  with  investigated and medicinal product (Drugs) and the speed with which this is done, are influenced in a major  way by the independent physician /clinicians undertaking the work .  Hence it is worth spreading time and trouble to choose investigator with care. The nature of the proposed study, will largely decide the professional and scientifically qualification and the patient and facilities required from the investigator.  Personal attributes are most important requirements for workers in drug trials or drug development. This may be decisive in choosing the particular doctor from a number similarly qualified scientifically. In many ways they are most important. Departure from the ideal in other respects can often be made good, but nothing can make up for serious deficiencies in personal qualities.  It is worth considering  in more  detail some of the  general advantages and disadvantages for drug research in the different  types of  centers available  of  co-operation  like research and academic  units, other department  in teaching hospitals , non-teaching hospitals , community heath and other  special  centers and general practitioner . There are many sharing points to the choice of particular investigator. he may will know  by publications and repute for previous  work  either with  the some type of drug  or in a special field of medicine or he may have worked with the company previously  or drug trials, occasionally he may approach the company to undertake studies and this forms a particularly  favorable  prognostic sign. He may be known socially and provincially .All of these diverse origins may be useful start to a relationship. Having satisfied scientifically and proficiently requirements are must look closely to personal factors. The personal nature of clinical investigator especially in relation to the company investigator’s own personality should be explored for the two will work closely together. A productively relationship is more likely when it is a harmonious one.  This mutual personal relationship is the key to successful trials and may lead one to work repeatedly on trials with the some investigator integrity, motivation, and reliability

Biography:

I am an assistant professor of Medical Microbiology, currently working at Mekelle University, Mekelle, Ethiopia. I completed my undergraduate (BSc in Medical Laboratory Sciences) and Post-graduate studies (MSc. in Medical Microbiology). I have presented MSc my research work in the 11th European Congress on Tropical Medicine and International Health, taking place in   Liverpool, UK on September 16 -20, 2019 (ECTMIH 2019). I am a Ph.D. student in Medical Microbiology since 2020 and I have published three of my Ph.D. research works. I am experienced in clinical laboratory service, teaching, community service and Scientific researches. In addition to this, I have published more than 19 research articles and one book chapter in peer reviewed and indexed Journals. Furthermore, I have awarded two research projects and one community service projects yet.

Abstract:

Statement of the problem: COVID-19 symptomatology in Africa appears significantly less serious than in the industrialized world. We and others previously postulated a partial explanation for this phenomenon, being a different, more activated immune system due to parasite infections. We investigated this hypothesis in an endemic area in Africa.                                    Methodology: Ethiopian COVID-19 patients were enrolled and screened for intestinal parasites, between July 2020 and March 2021. The primary outcome was the proportion of patients with severe COVID-19. SARS-CoV-2 infection was confirmed by RT-PCR on samples obtained from nasopharyngeal swabs, while direct microscopic examination, modified Ritchie concentration, and Kato-Katz methods were used to identify parasites and ova from a fresh stool sample. Ordinal logistic regression models were used to estimate the association between parasite infection and COVID-19 severity. Models were adjusted for sex, age, residence, education level, occupation, body mass index, and comorbidities. Data were analyzed using STATA version 14. P-value <0.05 was considered statistically significant. Findings: A total of 751 SARS-CoV-2 infected patients were enrolled, of whom 284 (37·8%) had an intestinal parasitic infection. Only 27/255 (10·6%) severe COVID-19 patients were co-infected with intestinal parasites, while 257/496 (51·8%) non-severe COVID-19 patients appeared parasite positive (p<0.0001). Patients co-infected with parasites had lower odds of developing severe COVID-19, with an adjusted odds ratio (AOR) of 0·14 (95% CI 0·09–0·24; p<0·0001) for all parasites, AOR 0·20 ([95% CI 0·11–0·38]; p<0·0001) for protozoa, and AOR 0·13 ([95% CI 0·07–0·26]; p<0·0001) for helminths. When stratified by species, co-infection with Entamoeba spp., Hymenolopis nana, and Schistosoma mansoni implied a lower probability of developing severe COVID-19. There were 11 deaths (1·5%), and all were among patients without parasites (p=0·009). Conclusions: Parasite co-infection is associated with a reduced risk of severe COVID-19 in African patients. Parasite-driven immunomodulatory responses may mute hyper-inflammation associated with severe COVID-19.