MedChem MOOC

Course: Medicinal Chemistry: The Molecular Basis of Drug Discovery
Length: 7 weeks
School/platform: Davidson/edX
Instructors: Erland Stevens

This medicinal chemistry course explores how chemists modify a molecule’s structure to design a safe and effective drug.
This course opens with a brief history of drug discovery and introduces the modern drug approval process. Then, we will transition to learning about receptors and enzymes, the body’s molecules most often targeted by drugs. We will also discuss the topics of pharmacokinetics (drug adsorption, elimination, and half-life) and metabolism. The course closes with units on how potential drug molecules are identified and subsequently optimized into safe and effective drugs.

Short version: nicely-done course, with lots of small, well-conceived extras.

I’ve realized for some time that a better understanding of chemistry, particularly organic chemistry, would help a lot with the biology courses I’ve been taking. Alas, I haven’t found an intro-level organic chemistry mooc, but I thought I might get some helpful exposure though this course, even though I’m more interested in how drugs affect biology than in optimizing drugs via lab analysis of their properties. I saw “some experience” with organic chem was recommended, so I spent a week trying to get a sense of the basics on Youtube (Leah Fisch’s vids, aka, were particularly helpful). I also found a Cerego set on functional groups (Cerego’s great for pure memorization and for keeping ideas from getting all dusty between moocs), but wasn’t optimistic about my chances of completing the course. Turns out I did fine, though I suspect my final score greatly exaggerates my overall comprehension. I did get some good exposure to heretofore unknown aspects of chemistry, which was the point. And it was interesting to see the process of drug development.

Each week included six or eight subtopics, each with a combination of video lectures, readings, and a few graded exercises, as well as an ungraded “virtual lab” offering practice in the concepts via computer modelling. Expert interviews closed the week: everything from a patent attorney (Fun Things to Do With a Chemistry Degree if you Don’t Want to Work in a Lab) and drug company CEO – both Davidson alumni – to research scientists specializing in the technical areas featured during the week . Three exams were spaced throughout the course, covering material from two or three weeks each.

I had some concerns early on that, because the course was created “in partnership” with a pharmaceutical company, that there would be some emphasis on the business side of drug development: defending pricing, cutting regulation, that sort of thing. No need to worry: although there was some mention of those factors in Week 1 in the overview of the drug development process, I never felt like an agenda was being pushed (and I’m pretty sensitive, to the point of paranoia, to agendas, especially now).

The second and third weeks were math-heavy, with Excel playing a central role. I’ve always avoided Excel as much as possible, but it was time to bite the bullet. Fortunately, there was plenty of explanation and great forum support. I had a very bad moment when I saw the phrase “area under the curve” – oh god, please don’t make me integrate – but it turned out to be simplified by another formula. Derivation of the formula was part of the material, but I was not in a position to really incorporate it. And that’s part of the reason I feel my comprehension wasn’t equal to my final grade. But I survived, if less nobly than was possible, and lived to fight another day in the sections on chemical bonds and reactions.

Discussion forums were active and helpful, with very prompt responses by Dr. Stevens himself. I’ve become very fond of many of the TAs and grad students who’ve handled discussion boards in various courses over the years, but there’s still something special, maybe because it’s becoming very rare, about the instructor covering the boards. I felt welcomed and supported in spite of my lack of technical background.

Another small extra with great impact: each lecture included a summary; not a transcript, which is available too, but a brief recap complete with clear diagrams. While hand-drawn diagrams are great during a lecture so you can see exactly what goes with what description, when it comes to putting something in my notes, a laser-printed typeset diagram beats a screen clip of a blackboard sketch every time. So the best of both worlds was provided.

Another greatly appreciated timesaver was the FAQ appended to each section. This was a combination of minor corrections to videos, more detailed instructions on various processes, and an accumulated knowledge contributed by forum discussion in previous sessions. I found the answer to many questions here, not to mention interesting extensions or applications of concepts introduced. I’ve never seen this before. If there’s a Best Practices for Moocs handbooks around, someone should add this one; it creates something like a culture for the course, across time.

Each of the brief introductory videos to each week was shot at a different location on the Davidson campus, with some link to the topic of the week: the dining hall kitchen for metabolism, a sports arena for competition. The PR for Davidson College probably doesn’t hurt, either. This is my second Davidson mooc, by the way (the first was in Digital Humanities, way on the other side of the aisle), and both have been very good.

Various databases and software packages, most online (the one that was download-only was in an optional Virtual Lab), came into play, including The Drug Bank, Molinspiration, and the Protein Data Bank. I’ve used similar packages, maybe the same ones through an interface, in my biology courses. Molinspiration particularly amused me: if you draw too many bonds on a given atom, it eventually asks: “Are you trying to draw a hedgehog?”

I picked up a great new vocabulary term. In addition to in vivo and in vitro (“in the organism” and “in the lab”), we now have in silico, “in computer simulation”. I don’t know why this strikes me so hilariously, but it does. It’s perfect!

A pre-test and post-test bracketed the course. Neither were graded beyond a single “extra credit” point for completion. The pre-test instructions emphasized that we weren’t expected to get the questions right; it wasn’t a prerequisite test, but merely a way to establish a starting benchmark. Good thing, since I had no idea what any of the questions were asking. The post-test came after a long, hard seven weeks, and while I was feeling overwhelmed by other courses besides. I made a half-hearted attempt at the first 10 of 15 before I decided I didn’t need the extra point that badly; I was feeling pretty discouraged about my retention of the material at that point.

I commented to that effect on the forums. Dr. Stevens replied with an explanation of how he used those scores, what he looked for in terms of a class “growth” average, and the formula used to calculate it. I was then more motivated to put some work into the last five questions. I regretted my slapdash approach to the first ten, in fact (see what a little pep talk can do? Yes, I’m an attention whore, but seriously, a little nudge works wonders), so I gave the final five a more serious shot. Given the equation, I figured if I got ¼ of the pretest correct merely by probability of multiple choice selection, all I needed to do was get seven of the post test correct to meet his hoped-for growth level. I’ll never know, since the scores aren’t revealed. I hope, at the very least, I didn’t drag down the group average too much. The course deserved better than that.

This was a great experience, even though my primary interest was more around the edges of the course focus. For those specifically interested in the drug development process, I’m thinking it’d be a great place to start.


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