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大家好~~很荣幸以本贴作为新一期小分队活动的kickoff。在下第一次发速度越障文，热切期盼各位的反馈和建议，谢谢！
速度阅读材料节选自
Small molecule drug discovery: why we need a paradigm shift
An interview with Professor Graeme Robertson
原文见附件
Source: Elsevier Pharma http://www.elsevierpharma.com/
(计时一 257 WORDS)
Professor Graeme Robertson is a university professor and co-founder of a small biotechnology company focused on developing new strategies for drug design. He explains why he believes the pharmaceutical drug discovery process needs to change direction, and soon…
Professor Robertson is currently Managing Director and co-founder of a small biotech company TES Pharma created and a research professor the University of Perugia, Italy. He has a detailed knowledge of the challenges of drug design gathered from over 24 years’ experience in drug discovery.
He worked for several years at GlaxoSmithKline, where he was responsible for investigating ion channels as potential drug targets and leading chemistry discovery in this area. He then moved to Siena Biotech S.p.A. as Vice President of Therapeutic Research and later became Vice President Portfolio Management, providing support for a portfolio of drug discovery targets.
Professor Robertson recently moved to the academic environment and, together with other members of the Department of Medicinal Chemistry and Drug Technologies at the University of Perugia, co-founded TES Pharma. The company plans to find new ways to integrate in depth knowledge of drug design and chemistry with basic biology in order to better design and develop effective disease modifiers via a network of world class centres of excellence.
Graeme shared with us his cross-industry perspective on an environment which is fast moving and prone to change, with topics ranging from the current challenges facing the pharmaceutical industry and where it’s heading, to the relationship between academia and pharma, and the ongoing interaction in research between biology and chemistry.
(计时二 254 WORDS)
Highlighting problems with current approaches to drug development
The pharmaceutical industry, thought by many to be recession-proof and able to carry on producing sustainable and increasing profits, is suffering under the pressure of global economic decline. This is illustrated by the large numbers of recent mergers and site closures in Europe, and the increased use of facilities in Asia.
“Early in my career I, like many others, believed that the pharmaceutical industry would be going strong no matter what… but currently this isn’t the case and serious revision of the drug discovery process is needed.
“A significant problem has been the emphasis on a business model and profits for shareholders rather than exploring the science to see where it can take us. There are several core problems: a lack of productivity, a lack of innovation and a failure to get a sufficient number of drugs through the pipeline. Productivity, that is NCEs from pharmaceutical companies has been particularly low in recent decades.”
The strategy that has predominated in small molecule drug discovery during the last few years has been a stepwise and linear approach that has relied on reverse chemical genetics to generate a range of potential lead compounds.
“People within the industry have assumed that putting more compounds into clinical trials would produce a successful drug, but there is little evidence that this is the case. We should not be putting more compounds into clinical trials, we should be putting better compounds into clinical trials.”
(计时三 228 WORDS)
Graeme believes that the process of developing drug candidates requires much better use of animal models and sharing of knowledge before moving into clinical trials.
“Clinical trials are something of a lottery now. If a candidate drug does not show the same effects in humans as it did in the animal model then little is done to revisit the models to improve their predictivity using data from the clinical setting. We don’t spend enough time going backwards to try to work out how we can best use the data generated in the clinical setting. This information could be invaluable in learning more about the drug and the disease process it is trying to target. Unfortunately, however, pharmaceutical companies often move on to pursue the ‘next big thing’, without learning why they are failing.”
Graeme admits there is no magical answer, but the drug discovery process needs to be changed, and radically so, if we are to revitalize drug discovery.
“We need to get away from the mind set of ‘go faster or with lower costs’. If we go faster we’re just going to hit the brick wall with more of a bang and it’ll hurt even more than it has already done because the process we are using just does not work.”
(计时四 220 WORDS)
In the current paradigm of drug development, individuals hard work is not adding up to corporate success.
“It is possible for an individual researcher within a drug company to be brilliant, hugely successful, highly motivated, and very productive but to add zero value to the company because they never work on a project that goes through to market. They are trying to add value, but they are failing and this is not their fault, or their company’s fault. It is really more of a reflection of how little we know about what we are doing in drug discovery.”
Another potential problem is that companies tend to link a target to a disease area far too early in the drug discovery process.
“We’re still way too reductionist in our approaches on selecting targets, and projects tend to be associated with a disease way too early. In our current pharmaceutical industry, compounds are developed for a predetermined product profile. What we should be doing is looking for good modulators of that target in a more disease independent fashion and then finding out the effect of modulating that target with our compounds. Decisions need to be made on the basis of our findings, and we need to stop following rigid research protocols blindly like machines.”
(计时五 269 WORDS)
Collaborative research and information exchange
Graeme, like many researchers, is inundated by new research papers on a daily basis and finds it difficult to keep up with the pace of developments.
“It is impossible to read all the papers you should read and although biology is relatively text-based, when you move into medicinal chemistry and drug design, you need to move beyond text searches. Being able to search structures would be ideal but it’s difficult to do that in any database outside Reaxys. I think this is the ideal model that we should be looking at as a way to interchange information on new drug candidates and their analogues.
“All electronic data associated with an article should be retrievable and searchable electronically, even screening information using pixel maps.”
Graeme foresees a time in the near future when it will be possible to search research papers by chemical structure with a sub-structure or similarity search, both in terms of the biology that is known about that structure, and any toxicology data.
“Electronic publishers are sitting on a mine of information; they are working on putting it into more useable databases for drug discovery research and, although it is a big task, I think they know how to do it.”
“There is widespread acceptance that change is inevitable, but we must first overcome the inertia that our fear of change creates. If publishers were to change the way they provide data so that this fuelled a knowledge seeking and knowledge sharing approach, this could be a great catalyst to get things moving.”
（计时结束）
越障练习
SOURCE: Science 24 February 2012: Vol. 335 no. 6071 pp. 932-933
http://www.sciencemag.org/content/335/6071/932.full
? Essays on Science and Society
A Season for Inquiry: Investigating Phenology in Local Campus Trees
[1242 WORDS – title excluded]
Michigan State University rightfully claims one of the most beautiful campuses in the Midwest. Each spring, we anticipate a commencement gilded with tulips and crabapple blossoms. In autumn, the campus beams with golden oaks and fiery maples. As a potential subject for inquiry learning, phenology, the study of recurrent natural events, is appealing for many reasons.
Phenologic studies have relatively few logistical constraints compared with many topics in biology. Virtually every habitat imaginable undergoes cyclical or seasonal changes that can be observed through local plants, animals, or other organisms. Documenting phenological patterns can be a straightforward and cost-effective strategy for engaging students in the science of observation with little need for additional equipment or supplies.
The subject of phenology is both timely and scientifically relevant. Interannual variability in factors such as temperature and precipitation can shift the timing of phenologic events by days to months, with realworld impacts ranging from ecosystem function (e.g., plant-pollinator interactions) to regional economies (e.g., agriculture and tourism). Larger-scale trends over long periods of time serve as important indicators of environmental changes, including climate change.
Finally, phenology is complex. Seemingly simple processes, such as the changing color of leaves, actually result from myriad interactions occurring across molecular- to ecosystem-level scales. As a complex system, phenology encompasses multiple biological processes that can be explored from diverse disciplinary perspectives across scales of space and time.
Our introductory labs are taught by graduate teaching assistants (TAs) ranging in both teaching experience and disciplinary expertise. As the real face of the lab, TAs bear immediate responsibility for motivating student learning and bringing new instructional strategies into the classroom. They recognized that the labs we had been teaching, in which students followed protocols to confirm known outcomes, did not reflect the biology that motivated each of us to become biologists. We believed that in order to change both the content and culture of our labs, we would need to fully engage TAs as collaborators in the reform process.
In summer 2008, we invited TAs to a 2-day “boot camp” to learn about evidence-based teaching practices and to provide input about goals for reforming labs. TAs said that labs should provide students opportunities to experience how science is done—not as a series of methodological steps, but as a way to ask questions, test ideas, and evaluate evidence. In addition, TAs wanted labs to be more authentic and to reflect the uncertainty of science as it is practiced. Students would pursue questions in which a “right” answer might not be known.
To incorporate these goals, TAs worked in small groups to rewrite existing labs, framing them as inquiry investigations with explicit and measurable learning objectives. Five TAs collaborated with us to take on the larger task of developing a new, semester-long phenology study, Campus Trees. Inspired by the citizenscientist model of the National Phenology Network, we envisioned the outgrowth of a long-term, student-generated database documenting phenology in our local campus trees. Our primary challenge was how to engage students in original inquiry, while at the same time, ensuring consistency and reliability in the student-generated data. Ultimately, we decided that students would mirror authentic ecological research by working collaboratively to design, field-test, and evaluate original methods for quantifying phenologic change.
In order to embed replication within the project design, we restricted the study to 200 trees representing four genera: Acer, Quercus, Malus, and Ginkgo. The Office of Campus Parks and Planning provided maps with locations and identification codes for all trees in the study. Students working in groups of four were assigned three trees to study for the semester; each tree was independently sampled by at least three different student groups across different lab sections. Students would not know that others were studying “their” trees until later in the semester.
Students began by locating their trees in the field, making detailed sketches about location and identifying characteristics, and recording tree height and diameter. Students had 2 weeks to brainstorm alternative approaches for quantifying color change and leaf fall and then present their proposals in class. Feedback from classmates and TAs helped students clarify study objectives and solidify their data collection plans.
For the next several weeks, students applied their methods in the field and managed all logistical and troubleshooting issues that arose. After leaves had fallen, students uploaded their final data and methods to our course-management system, LON-CAPA. Students used their tree codes to search for and retrieve the data and methods of other groups that had studied the same trees. In a final presentation, students evaluated alternative methods and compared the quality of data produced. Groups wrote short papers based on their analyses and proposed an “ideal” method that would best meet the criteria for (i) producing reliable and accurate phenologic data, (ii) generating high-quality data that can be used in future research, and (iii) feasible implementation in a course enrolling large numbers of students (up to 1000 per semester).
What did we learn from this experience? First, students are capable of achieving far more than we expect. Our concern that students might converge on a common approach was not realized. In fact, students used diverse and innovative methods for data collection [e.g., determining which branches to sample using a Twister spinner, quantifying leaf color with electronic color-pickers and RGB (red-green-blue) codes] and for troubleshooting (e.g., What should you do if the landscaping staff prunes the branches you were sampling? Should a leaf be counted in your sample if it's half eaten?). Another concern—that students would regard their own method as “best” and not critically evaluate alternatives—was also not realized. In their final analyses, few groups suggested that they had developed an ideal method and, instead, weighed strengths and weaknesses of multiple methods. TAs noted that by the end of the semester, students better understood how nuances in experimental approach could have an impact on both the nature and interpretation of data—an important benchmark in the development of science literacy.
Second, TAs have much to offer in terms of innovating curricula and providing insights that can improve students' learning experiences. Our TAs cared deeply about the quality of their students' learning and took pride in their successes. However, in order to realize the potential of TAs to rejuvenate labs, programs must be willing to liberate some creative control and to provide substantial mentoring along the way. Inquiry teaching is not easy and represents a significant departure from traditional, lecturebased instruction. TAs' transition to inquiry teaching involved discussing real examples in practice. Iterative feedback and a supportive network of peers also helped TAs develop confidence in their classrooms. Our program included TAs in decision-making about curricula and acknowledged authorship on TA-developed materials. This can do much to illustrate the value of TA input, not to mention bolstering TAs' curriculum vitae and teaching portfolios.
Finally, we advocate for including creativity in the reward structure of college-level biology. Confirmatory labs do not provide sufficient opportunities for students to experience the cycles of failure and recovery that practicing scientists experience as an ordinary part of scientific inquiry. Indeed, learning how to deploy creative strategies for managing the unexpected is a critical part of becoming a scientist yet is rarely reflected in most lab curricula. If we truly want to cultivate a nation of problem-solvers, we must allow students opportunities to wrestle with real problems and be rewarded for conceiving creative strategies for solving them. Our students have shown us they are ready for the challenge. |
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发表于 2012-2-27 16:07:58
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