BIOENGR C101
Engineering Principles for Drug Delivery
Description: Lecture, four hours; discussion, one hour; outside study, seven hours. Enforced requisites: Mathematics 33B, Physics 1B. Application of engineering principles for designing and understanding delivery of therapeutics. Discussion of physics and mathematics required for understanding colloidal stability. Analysis of concepts related to both modeling and experimentation of endocytosis and intracellular trafficking mechanisms. Analysis of diffusion of drugs, coupled with computational and engineering mathematics approaches. Concurrently scheduled with course C201. Letter grading.
Units: 4.0
Units: 4.0
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Most Helpful Review
Winter 2020 - I took this class for the Engineering Science tech breadth having only satisfied the minimum prerequisites: Math 33B and Physics 1B, as a sophomore. Despite my minimal background in Bioengineering, I found the class to be very manageable and highly interesting, and I ended up getting an A. This class was easier and less time-consuming than many lower divs (but definitely not easy). If you’re a ChemE, think of it as a Ch Engr 101A/109 Combo course with some electrochemistry on the side. Dr. Kamei has a distinguished teaching award, and it shows; he's a phenomenal lecturer. He definitely cares about whether his students learn, and he explains very well. He teaches math better than most math professors do :) About the logistics about the class: You must show up to lecture, and you must print out the slides or bring a tablet. You should also read the lecture slides beforehand, to not be lost during class. The slides are NOT a way to skip lecture. Dr. Kamei talks about stuff that are not on the slides, and he sets up the vast majority of his proofs by writing on the whiteboard. Besides missing out on critical information and examples, Kamei's lecturing skills would be wasted if you don't go to lecture. So go to lecture. Next, as a heads-up, this is a math-heavy class, which can be split into three parts. The first part is electrostatic modeling of nanoparticles. The second part is numerical methods of solving differential equations, and the third part is fluid dynamics. While the class (and the syllabus) can seem intimidating at first, don't be scared. It's a ton of math, but Kamei is very good at teaching, and both him and the TAs are very helpful during office hours. You will be fine if you don't have a background in Bioengineering. Besides the prerequisites, all you really need are basic coding skills and a basic knowledge of biology. The exams were definitely difficult; you need to be able to do homework-level questions quickly alongside knowing concepts. That said, the homework was definitely on the level of the exams, and you get a plethora of old exam questions to practice with. Even better, the homework only took a few hours per week. There was also a numerical methods project in the middle of the quarter which was decently time-consuming, but definitely a grade booster provided you followed the directions. Again, Kamei is willing to help out in case of difficulties in terms of the projects. Tl;dr: Don't be scared to take this class if you hear about Kamei's reputation as a hard professor and/or if you lack a background in Bioengineering. Also, even though this class appears to be offered only once every few years, it's worth taking. He's that good at teaching.
Winter 2020 - I took this class for the Engineering Science tech breadth having only satisfied the minimum prerequisites: Math 33B and Physics 1B, as a sophomore. Despite my minimal background in Bioengineering, I found the class to be very manageable and highly interesting, and I ended up getting an A. This class was easier and less time-consuming than many lower divs (but definitely not easy). If you’re a ChemE, think of it as a Ch Engr 101A/109 Combo course with some electrochemistry on the side. Dr. Kamei has a distinguished teaching award, and it shows; he's a phenomenal lecturer. He definitely cares about whether his students learn, and he explains very well. He teaches math better than most math professors do :) About the logistics about the class: You must show up to lecture, and you must print out the slides or bring a tablet. You should also read the lecture slides beforehand, to not be lost during class. The slides are NOT a way to skip lecture. Dr. Kamei talks about stuff that are not on the slides, and he sets up the vast majority of his proofs by writing on the whiteboard. Besides missing out on critical information and examples, Kamei's lecturing skills would be wasted if you don't go to lecture. So go to lecture. Next, as a heads-up, this is a math-heavy class, which can be split into three parts. The first part is electrostatic modeling of nanoparticles. The second part is numerical methods of solving differential equations, and the third part is fluid dynamics. While the class (and the syllabus) can seem intimidating at first, don't be scared. It's a ton of math, but Kamei is very good at teaching, and both him and the TAs are very helpful during office hours. You will be fine if you don't have a background in Bioengineering. Besides the prerequisites, all you really need are basic coding skills and a basic knowledge of biology. The exams were definitely difficult; you need to be able to do homework-level questions quickly alongside knowing concepts. That said, the homework was definitely on the level of the exams, and you get a plethora of old exam questions to practice with. Even better, the homework only took a few hours per week. There was also a numerical methods project in the middle of the quarter which was decently time-consuming, but definitely a grade booster provided you followed the directions. Again, Kamei is willing to help out in case of difficulties in terms of the projects. Tl;dr: Don't be scared to take this class if you hear about Kamei's reputation as a hard professor and/or if you lack a background in Bioengineering. Also, even though this class appears to be offered only once every few years, it's worth taking. He's that good at teaching.
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