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In 2015, researchers at UCI published a paper demonstrating some success uncooking egg proteins! Link is in comments.(Captions at top of full Reels) #todayiLearned #TIL #science #biotech #biotechnology #drugdevelopment #proteinproduction #cellculture

🤣 - Mice are small, agile rodents belonging to the family Muridae. They are characterized by their rounded ears, long tails, and sharp, curved teeth that are adapted for gnawing. Common species of mice include the house mouse (*Mus musculus*), which is prevalent in human environments, and the field mouse, which is found in agricultural and grassy areas. Mice have adapted to a wide range of habitats and are found on every continent except Antarctica. Their small size and ability to reproduce rapidly make them highly successful and widespread. Mice play a significant role in ecosystems as both prey and pest. In the wild, they are a crucial food source for many predators, including birds of prey, snakes, and larger mammals. Their burrowing and nesting habits also contribute to soil aeration and seed dispersal. However, when they invade human homes and businesses, mice can become pests, causing damage to property and food supplies. They are known for their ability to squeeze through small openings and their tendency to chew on electrical wires and other materials, which can lead to fire hazards. In addition to their ecological impact, mice have been instrumental in scientific research. Due to their genetic, biological, and behavioral similarities to humans, they are commonly used as model organisms in studies of genetics, disease, and drug development. Mice have contributed significantly to our understanding of various health conditions, including cancer, diabetes, and neurological disorders. Their role in research has provided valuable insights that have advanced medical science and improved human health.

The deadliest dr*g💀 #motivation #psychologyquotes #frankunderwood #motivationalquotes #manipulation #elitemindset #

It’s never too late. cc: Bojack #hopecore #mindset #mentality #bojackhorseman

animation from RCSB Protein Data Bank in collab with PDB-101. article by Choi, Rempala, & Kim, 2017, in Scientific Reports, Beyond the Michaelis-Menten equation: Accurate and efficient estimation of enzyme kinetic parameters (i was in a michaelis-menten mood ig) "Because enzymes can modulate biochemical reaction rates by selectively catalyzing specific substrates1, they play fundamental roles in metabolism, signal transduction, and cell regulation, and their malfunction can cause serious diseases. Furthermore, enzymes have been used as extremely specific catalysts in diverse industrial fields such as drug development, biofuel production, and food processing. A canonical approach used to understand enzyme kinetics for a century has been based on the Michaelis-Menten equation (MM equation), which was developed by Michaelis and Menten and then was more rigorously derived by Briggs and Haldane using the standard quasi-steady-state approximation (sQSSA). The equation describes the dependence of enzyme-catalyzed reaction rates on the concentration of substrate by using two parameters, the catalytic constant, k cat and the Michaelis-Menten constant, K M (see below for details). The k cat determines the maximum rate of the reaction at saturating substrate concentrations, V max = k cat E T, where E T is total enzyme concentration, and the K M is the substrate concentration at which the reaction rate is half of V max. There are two major assays to estimate k cat and K M from a measured accumulation of product over time (i.e. progress curve): the initial velocity assay (initial rate analysis) and the reaction progress curve assay (progress curve analysis). For the initial velocity assay, initial rates of the reaction are measured for a range of substrate concentrations. Then, by using a linear transform of these data, such as Lineweaver-Burk plots, the two parameters can be easily estimated without use of any computational tools." #biochem #enzymes #kinetics

AI is changing the game in drug development! Exscientia's breakthrough in treating an 82-year-old's resistant blood cancer shows how personalized treatments and faster discoveries are now within reach. 💊 #AI #AITechnology #Medicine

Anne looks the same 😳 🎥 Love & other drugs: Maggie is an alluring free spirit who won’t let anyone – or anything – tie her down. But she meets her match in Jamie, whose relentless and nearly infallible charm serves him well with the ladies and the cutthroat world of pharmaceutical sales. Maggie and Jamie’s evolving relationship takes them both by surprise, as they find themselves under the influence of the ultimate drug: love. 📺 watch on: Disney plus and Netflix #explorepage #explorepost #funnymemes #memes #memestagram #memesdaily #wholesome #wholesomememes #fashion #fashionstyle #jokes #movie #movies #viralmovies

MIT finance professor Andrew W. Lo, an expert in healthcare finance, emphasizes in his Healthcare Finance lectures and research that financial markets play an essential role in drug development . He explains that clinical trials often span 10–15 years and cost hundreds of millions, so innovative funding mechanisms—such as equity financings, securitized debt vehicles, or biotech “megafunds”—are crucial to attract patient capital. 🚀 No Signals. Just Real Analytics. Be the first to download MacroGlide App. Get Early Access — FREE (LINK IN BIO). Credits: Andrew Lo, OpenCoursWave, 2025 Use: Edited for educational purposes. No ownership claimed.
Top Creators
Most active in #drug-development
Reels Graph Intelligence.
Advanced mapping of high-affinity Instagram Reels semantic patterns identified within the #drug-development ecosystem.
Strategic Implementation
Our semantic engine has identified these specific pattern clusters as high-affinity matches for #drug-development. Integrated usage of #drug-development with strategic Reels tags like #development and #developer is statistically linked to a significant increase in initial Reels discovery velocity.
In-Depth Hashtag Analysis: #drug-development
Expert Review • June 5, 2026 • Based on 12 Reels
Executive Overview
#drug-development is an actively used Instagram hashtag. Across the 12 trending reels analyzed on this page, the content has accumulated a combined total of 38,440,510 views— demonstrating exceptional viral potential within this content vertical. The top creator ecosystem features 8 notable accounts, led by @netflixnmovies with 11,591,093 total views. The hashtag's semantic network includes 10 related keywords such as #development, #developer, #developers, indicating its position within a broader content cluster.
Viewership & Reach Analysis
The 12 reels in this dataset have generated a combined 38,440,510 views, translating to an average of 3,203,376 views per reel. This exceptionally high average viewership indicates that content in this hashtag frequently hits the Explore page or Reels tab, driving massive exposure beyond the creator's immediate follower base.
The highest-performing reel in this dataset received 11,591,093 views. This viral outlier performance is 362% of the average reel performance in this set. This significant gap between the top performer and the average highlights the "viral lottery" nature of this hashtag — breakout hits can achieve massive scale.
Content Overview & Top Creators
The #drug-development ecosystem is dominated by short-form video content (Reels), aligning with Instagram's algorithmic preference for video-first distribution. There are 8 distinct accounts contributing to the trending feed. The top creator, @netflixnmovies, has contributed 1 reel with a total viewership of 11,591,093. The top three creators — @netflixnmovies, @kristinakuzmic, and @wasted — together account for 80.9% of the total views in this dataset. The semantic network of #drug-development extends across 10 related hashtags, including #development, #developer, #developers, #develop. Creators often use these tags together to reach overlapping audiences.
Discoverability & Reach Potential
The discoverability metrics for #drug-development indicate an active content ecosystem. The average of 3,203,376 views per reel demonstrates consistent audience reach. For creators using #drug-development, high-quality production and strong hooks in the first 1-2 seconds tend to perform best given the competition.
Analyst Verdict
#drug-development demonstrates the hallmarks of a well-performing Instagram hashtag. With an average of 3,203,376 views per reel, the viewership metrics position this hashtag as a premium discovery vehicle. Creators like @netflixnmovies and @kristinakuzmic are leading the charge, setting viewership benchmarks for the community.
Frequently Asked Questions
Everything about #drug-development on Instagram
Global Reels Trends
Explore high-velocity Instagram Reels hashtags currently shaping global discovery.














