[{"data":1,"prerenderedAt":813},["ShallowReactive",2],{"blog-posts":3},[4,422],{"id":5,"title":6,"author":7,"body":8,"date":407,"description":408,"draft":409,"extension":410,"image":411,"meta":412,"navigation":413,"path":414,"seo":415,"stem":416,"tags":417,"__hash__":421},"blog/blog/ai-on-modern-instruments.md","AI on Modern Analytical Instruments","Adam",{"type":9,"value":10,"toc":400},"minimark",[11,16,20,32,39,43,46,49,171,174,178,181,184,213,352,356,359,362,377,383,386,390,393,396],[12,13,15],"h2",{"id":14},"the-interface-problem-in-modern-labs","The interface problem in modern labs",[17,18,19],"p",{},"Most analytical instruments today still require scientists to navigate deep menus of parameters, manually configure run sequences, and translate their experimental intent into the language the machine understands. This is backwards.",[17,21,22,23,27,28,31],{},"The scientist knows ",[24,25,26],"em",{},"what"," they want to measure. The instrument knows ",[24,29,30],{},"how"," to measure it. The gap between intent and execution is filled with button clicks, dropdown menus, and parameter tables that haven't fundamentally changed in decades.",[33,34,36],"callout",{"type":35},"info",[17,37,38],{},"Surface Plasmon Resonance (SPR) measures molecular binding kinetics in real-time without labels, making it the gold standard for interaction analysis in drug discovery.",[12,40,42],{"id":41},"from-parameters-to-intent","From parameters to intent",[17,44,45],{},"What if you could describe an experiment the way you'd describe it to a colleague?",[17,47,48],{},"Instead of manually setting flow rates, contact times, regeneration conditions, and concentration series, imagine declaring your experimental intent:",[50,51,56],"pre",{"className":52,"code":53,"language":54,"meta":55,"style":55},"language-python shiki shiki-themes 2026 Dark 2026 Dark","experiment = {\n    \"analyte\": \"mAb-123\",\n    \"ligand\": \"Protein-A\",\n    \"concentrations\": [1, 3, 10, 30, 100],\n    \"unit\": \"nM\",\n    \"regeneration\": \"glycine-pH2\"\n}\n","python","",[57,58,59,75,91,104,141,154,165],"code",{"__ignoreMap":55},[60,61,64,68,72],"span",{"class":62,"line":63},"line",1,[60,65,67],{"class":66},"snv8h","experiment ",[60,69,71],{"class":70},"srH4v","=",[60,73,74],{"class":66}," {\n",[60,76,78,82,85,88],{"class":62,"line":77},2,[60,79,81],{"class":80},"skZ57","    \"analyte\"",[60,83,84],{"class":66},": ",[60,86,87],{"class":80},"\"mAb-123\"",[60,89,90],{"class":66},",\n",[60,92,94,97,99,102],{"class":62,"line":93},3,[60,95,96],{"class":80},"    \"ligand\"",[60,98,84],{"class":66},[60,100,101],{"class":80},"\"Protein-A\"",[60,103,90],{"class":66},[60,105,107,110,113,117,120,123,125,128,130,133,135,138],{"class":62,"line":106},4,[60,108,109],{"class":80},"    \"concentrations\"",[60,111,112],{"class":66},": [",[60,114,116],{"class":115},"sEQcL","1",[60,118,119],{"class":66},", ",[60,121,122],{"class":115},"3",[60,124,119],{"class":66},[60,126,127],{"class":115},"10",[60,129,119],{"class":66},[60,131,132],{"class":115},"30",[60,134,119],{"class":66},[60,136,137],{"class":115},"100",[60,139,140],{"class":66},"],\n",[60,142,144,147,149,152],{"class":62,"line":143},5,[60,145,146],{"class":80},"    \"unit\"",[60,148,84],{"class":66},[60,150,151],{"class":80},"\"nM\"",[60,153,90],{"class":66},[60,155,157,160,162],{"class":62,"line":156},6,[60,158,159],{"class":80},"    \"regeneration\"",[60,161,84],{"class":66},[60,163,164],{"class":80},"\"glycine-pH2\"\n",[60,166,168],{"class":62,"line":167},7,[60,169,170],{"class":66},"}\n",[17,172,173],{},"The instrument understands the context. It knows what flow rates produce clean kinetics for this analyte class. It knows the optimal contact time for reliable curve fitting. It can adapt regeneration conditions based on real-time surface stability monitoring.",[12,175,177],{"id":176},"what-self-driving-means-for-biophysics","What self-driving means for biophysics",[17,179,180],{},"Self-driving doesn't mean removing the scientist from the loop. It means elevating their role from machine operator to experiment designer.",[17,182,183],{},"A self-driving SPR instrument:",[185,186,187,195,201,207],"ul",{},[188,189,190,194],"li",{},[191,192,193],"strong",{},"Plans"," the experiment sequence from a high-level declaration",[188,196,197,200],{},[191,198,199],{},"Adapts"," in real-time based on data quality signals",[188,202,203,206],{},[191,204,205],{},"Validates"," results against expected binding models",[188,208,209,212],{},[191,210,211],{},"Reports"," findings in the context of the experimental question",[50,214,218],{"className":215,"code":216,"language":217,"meta":55,"style":55},"language-yaml shiki shiki-themes 2026 Dark 2026 Dark","# Declarative experiment configuration\nmethod:\n  type: kinetics\n  analyte: mAb-123\n  ligand: Protein-A\n  design: single-cycle\n  concentrations:\n    values: [1, 3, 10, 30, 100]\n    unit: nM\n  quality:\n    min_rmax: 20\n    max_chi2: 1.0\n","yaml",[57,219,220,226,235,245,255,265,275,282,311,322,330,341],{"__ignoreMap":55},[60,221,222],{"class":62,"line":63},[60,223,225],{"class":224},"sI3U9","# Declarative experiment configuration\n",[60,227,228,232],{"class":62,"line":77},[60,229,231],{"class":230},"sV7Mv","method",[60,233,234],{"class":66},":\n",[60,236,237,240,242],{"class":62,"line":93},[60,238,239],{"class":230},"  type",[60,241,84],{"class":66},[60,243,244],{"class":80},"kinetics\n",[60,246,247,250,252],{"class":62,"line":106},[60,248,249],{"class":230},"  analyte",[60,251,84],{"class":66},[60,253,254],{"class":80},"mAb-123\n",[60,256,257,260,262],{"class":62,"line":143},[60,258,259],{"class":230},"  ligand",[60,261,84],{"class":66},[60,263,264],{"class":80},"Protein-A\n",[60,266,267,270,272],{"class":62,"line":156},[60,268,269],{"class":230},"  design",[60,271,84],{"class":66},[60,273,274],{"class":80},"single-cycle\n",[60,276,277,280],{"class":62,"line":167},[60,278,279],{"class":230},"  concentrations",[60,281,234],{"class":66},[60,283,285,288,290,292,294,296,298,300,302,304,306,308],{"class":62,"line":284},8,[60,286,287],{"class":230},"    values",[60,289,112],{"class":66},[60,291,116],{"class":115},[60,293,119],{"class":66},[60,295,122],{"class":115},[60,297,119],{"class":66},[60,299,127],{"class":115},[60,301,119],{"class":66},[60,303,132],{"class":115},[60,305,119],{"class":66},[60,307,137],{"class":115},[60,309,310],{"class":66},"]\n",[60,312,314,317,319],{"class":62,"line":313},9,[60,315,316],{"class":230},"    unit",[60,318,84],{"class":66},[60,320,321],{"class":80},"nM\n",[60,323,325,328],{"class":62,"line":324},10,[60,326,327],{"class":230},"  quality",[60,329,234],{"class":66},[60,331,333,336,338],{"class":62,"line":332},11,[60,334,335],{"class":230},"    min_rmax",[60,337,84],{"class":66},[60,339,340],{"class":115},"20\n",[60,342,344,347,349],{"class":62,"line":343},12,[60,345,346],{"class":230},"    max_chi2",[60,348,84],{"class":66},[60,350,351],{"class":115},"1.0\n",[12,353,355],{"id":354},"the-convergence-of-ai-and-instrumentation","The convergence of AI and instrumentation",[17,357,358],{},"Large language models are not going to replace analytical chemists or biophysicists. But they are going to change how scientists interact with their tools.",[17,360,361],{},"When an instrument has a semantic understanding of the experiment being run, it can:",[363,364,365,368,371,374],"ol",{},[188,366,367],{},"Suggest experimental designs based on literature precedent",[188,369,370],{},"Identify anomalies in real-time and suggest corrective actions",[188,372,373],{},"Generate publication-ready reports from raw data",[188,375,376],{},"Learn from previous experiments to optimize future runs",[33,378,380],{"type":379},"tip",[17,381,382],{},"The best instrument interface is one that disappears. The scientist thinks about science, and the instrument handles the rest.",[17,384,385],{},"This is the future we're building at Instromeda. Not instruments with chatbots bolted on, but instruments where intelligence is fundamental to the measurement architecture.",[12,387,389],{"id":388},"what-comes-next","What comes next",[17,391,392],{},"The transition from parameter-driven to intent-driven instruments won't happen overnight. It requires rethinking not just the software interface, but the hardware architecture, the data pipeline, and the relationship between the scientist and their tools.",[17,394,395],{},"We believe the instruments of the next decade will be defined not by their optical sensitivity or fluidic precision alone, but by their ability to understand what the scientist is trying to achieve and autonomously deliver the answer.",[397,398,399],"style",{},"html pre.shiki code .snv8h, html code.shiki .snv8h{--shiki-default:#BBBEBF;--shiki-dark:#BBBEBF}html pre.shiki code .srH4v, html code.shiki .srH4v{--shiki-default:#FF7B72;--shiki-dark:#FF7B72}html pre.shiki code .skZ57, html code.shiki .skZ57{--shiki-default:#A5D6FF;--shiki-dark:#A5D6FF}html pre.shiki code .sEQcL, html code.shiki .sEQcL{--shiki-default:#79C0FF;--shiki-dark:#79C0FF}html .default .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}html.dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}html pre.shiki code .sI3U9, html code.shiki .sI3U9{--shiki-default:#8B949E;--shiki-dark:#8B949E}html pre.shiki code .sV7Mv, html code.shiki .sV7Mv{--shiki-default:#7EE787;--shiki-dark:#7EE787}",{"title":55,"searchDepth":77,"depth":77,"links":401},[402,403,404,405,406],{"id":14,"depth":77,"text":15},{"id":41,"depth":77,"text":42},{"id":176,"depth":77,"text":177},{"id":354,"depth":77,"text":355},{"id":388,"depth":77,"text":389},"2025-06-15","How conversational AI is changing the way scientists interact with lab hardware - from rigid parameter entry to natural language experiment design.",false,"md",null,{},true,"/blog/ai-on-modern-instruments",{"title":6,"description":408},"blog/ai-on-modern-instruments",[418,419,420],"AI","instrumentation","lab-automation","HqOrVxIu8xk6SqzQ69K-gb3Uc-c0oMwFZdKaH6lPzwo",{"id":423,"title":424,"author":7,"body":425,"date":802,"description":803,"draft":409,"extension":410,"image":411,"meta":804,"navigation":413,"path":805,"seo":806,"stem":807,"tags":808,"__hash__":812},"blog/blog/what-is-spr.md","What is Surface Plasmon Resonance?",{"type":9,"value":426,"toc":795},[427,431,449,452,457,461,464,495,637,644,648,651,707,710,718,723,727,730,750,753,757,760,786,789,792],[12,428,430],{"id":429},"the-gold-standard-for-binding-kinetics","The gold standard for binding kinetics",[17,432,433,434,437,438,441,442,444,445,448],{},"Surface Plasmon Resonance (SPR) is a label-free, real-time technique for measuring molecular interactions. It tells you not just ",[24,435,436],{},"whether"," two molecules bind, but ",[24,439,440],{},"how fast"," they associate, ",[24,443,440],{}," they dissociate, and ",[24,446,447],{},"how tightly"," they hold on.",[17,450,451],{},"In drug discovery, these kinetic parameters are critical. A drug candidate might bind its target with high affinity, but if the kinetics are wrong -- too slow to associate, too fast to dissociate -- it may fail in the clinic.",[33,453,454],{"type":35},[17,455,456],{},"SPR measures changes in refractive index near a gold surface as molecules bind and unbind. No fluorescent labels. No radioactive tracers. Just physics.",[12,458,460],{"id":459},"how-spr-works","How SPR works",[17,462,463],{},"At its core, SPR exploits the physics of light interacting with a thin gold film:",[363,465,466,472,479,486,492],{},[188,467,468,471],{},[191,469,470],{},"Polarized light"," hits a gold-coated sensor surface at a specific angle",[188,473,474,475,478],{},"At the ",[191,476,477],{},"resonance angle",", energy transfers to surface plasmons (collective electron oscillations)",[188,480,481,482,485],{},"This creates a ",[191,483,484],{},"dip in reflected light"," at a precise angle",[188,487,488,489],{},"When molecules bind to the surface, the ",[191,490,491],{},"local refractive index changes",[188,493,494],{},"The resonance angle shifts, and this shift is measured in real-time",[50,496,498],{"className":52,"code":497,"language":54,"meta":55,"style":55},"# Simplified binding response calculation\ndef spr_response(kon, koff, concentration, time, rmax):\n    \"\"\"Calculate SPR response using 1:1 Langmuir model.\"\"\"\n    kobs = kon * concentration + koff\n    req = rmax * (kon * concentration) / (kon * concentration + koff)\n    return req * (1 - math.exp(-kobs * time))\n",[57,499,500,505,544,549,571,605],{"__ignoreMap":55},[60,501,502],{"class":62,"line":63},[60,503,504],{"class":224},"# Simplified binding response calculation\n",[60,506,507,510,514,517,521,523,526,528,531,533,536,538,541],{"class":62,"line":77},[60,508,509],{"class":70},"def",[60,511,513],{"class":512},"sYGIp"," spr_response",[60,515,516],{"class":66},"(",[60,518,520],{"class":519},"s_i6V","kon",[60,522,119],{"class":66},[60,524,525],{"class":519},"koff",[60,527,119],{"class":66},[60,529,530],{"class":519},"concentration",[60,532,119],{"class":66},[60,534,535],{"class":519},"time",[60,537,119],{"class":66},[60,539,540],{"class":519},"rmax",[60,542,543],{"class":66},"):\n",[60,545,546],{"class":62,"line":93},[60,547,548],{"class":80},"    \"\"\"Calculate SPR response using 1:1 Langmuir model.\"\"\"\n",[60,550,551,554,556,559,562,565,568],{"class":62,"line":106},[60,552,553],{"class":66},"    kobs ",[60,555,71],{"class":70},[60,557,558],{"class":66}," kon ",[60,560,561],{"class":70},"*",[60,563,564],{"class":66}," concentration ",[60,566,567],{"class":70},"+",[60,569,570],{"class":66}," koff\n",[60,572,573,576,578,581,583,586,588,591,594,596,598,600,602],{"class":62,"line":143},[60,574,575],{"class":66},"    req ",[60,577,71],{"class":70},[60,579,580],{"class":66}," rmax ",[60,582,561],{"class":70},[60,584,585],{"class":66}," (kon ",[60,587,561],{"class":70},[60,589,590],{"class":66}," concentration) ",[60,592,593],{"class":70},"/",[60,595,585],{"class":66},[60,597,561],{"class":70},[60,599,564],{"class":66},[60,601,567],{"class":70},[60,603,604],{"class":66}," koff)\n",[60,606,607,610,613,615,618,620,623,626,629,632,634],{"class":62,"line":156},[60,608,609],{"class":70},"    return",[60,611,612],{"class":66}," req ",[60,614,561],{"class":70},[60,616,617],{"class":66}," (",[60,619,116],{"class":115},[60,621,622],{"class":70}," -",[60,624,625],{"class":66}," math.exp(",[60,627,628],{"class":70},"-",[60,630,631],{"class":66},"kobs ",[60,633,561],{"class":70},[60,635,636],{"class":66}," time))\n",[17,638,639,640,643],{},"The result is a ",[191,641,642],{},"sensorgram"," -- a plot of response units (RU) over time that shows the complete binding event: baseline, association, steady-state, and dissociation.",[12,645,647],{"id":646},"key-parameters-from-spr","Key parameters from SPR",[17,649,650],{},"From a single experiment, SPR delivers three fundamental binding parameters:",[652,653,654,670],"table",{},[655,656,657],"thead",{},[658,659,660,664,667],"tr",{},[661,662,663],"th",{},"Parameter",[661,665,666],{},"Symbol",[661,668,669],{},"What it tells you",[671,672,673,685,696],"tbody",{},[658,674,675,679,682],{},[676,677,678],"td",{},"Association rate",[676,680,681],{},"k_on",[676,683,684],{},"How fast molecules bind",[658,686,687,690,693],{},[676,688,689],{},"Dissociation rate",[676,691,692],{},"k_off",[676,694,695],{},"How fast molecules release",[658,697,698,701,704],{},[676,699,700],{},"Equilibrium dissociation constant",[676,702,703],{},"K_D",[676,705,706],{},"Overall binding affinity",[17,708,709],{},"These parameters are related by a simple equation:",[50,711,716],{"className":712,"code":714,"language":715},[713],"language-text","K_D = k_off / k_on\n","text",[57,717,714],{"__ignoreMap":55},[33,719,720],{"type":379},[17,721,722],{},"A low K_D means tight binding. But two molecules can have the same K_D with very different kinetics. SPR reveals the full picture.",[12,724,726],{"id":725},"why-spr-matters-for-drug-discovery","Why SPR matters for drug discovery",[17,728,729],{},"Affinity alone doesn't predict drug efficacy. The kinetics matter:",[185,731,732,738,744],{},[188,733,734,737],{},[191,735,736],{},"Slow k_off"," (long residence time) often correlates with better in vivo efficacy",[188,739,740,743],{},[191,741,742],{},"Fast k_on"," improves target engagement under physiological conditions",[188,745,746,749],{},[191,747,748],{},"Kinetic selectivity"," can distinguish between closely related targets",[17,751,752],{},"SPR provides this kinetic resolution without perturbing the molecules being studied. No labels means no steric interference, no quenching artifacts, and no false negatives from label placement.",[12,754,756],{"id":755},"where-spr-is-heading","Where SPR is heading",[17,758,759],{},"The next generation of SPR instruments will be defined by:",[185,761,762,768,774,780],{},[188,763,764,767],{},[191,765,766],{},"Automation"," -- removing manual sample preparation and injection bottlenecks",[188,769,770,773],{},[191,771,772],{},"Intelligence"," -- real-time data quality monitoring and adaptive experiment control",[188,775,776,779],{},[191,777,778],{},"Throughput"," -- measuring hundreds of interactions per day without sacrificing data quality",[188,781,782,785],{},[191,783,784],{},"Accessibility"," -- making kinetic characterization available earlier in the discovery pipeline",[17,787,788],{},"The instruments of tomorrow won't just measure binding. They'll understand the experiment, optimize conditions on the fly, and deliver publication-ready results with minimal human intervention.",[17,790,791],{},"That's the vision driving Instromeda.",[397,793,794],{},"html pre.shiki code .sI3U9, html code.shiki .sI3U9{--shiki-default:#8B949E;--shiki-dark:#8B949E}html pre.shiki code .srH4v, html code.shiki .srH4v{--shiki-default:#FF7B72;--shiki-dark:#FF7B72}html pre.shiki code .sYGIp, html code.shiki .sYGIp{--shiki-default:#D2A8FF;--shiki-dark:#D2A8FF}html pre.shiki code .snv8h, html code.shiki .snv8h{--shiki-default:#BBBEBF;--shiki-dark:#BBBEBF}html pre.shiki code .s_i6V, html code.shiki .s_i6V{--shiki-default:#C9D1D9;--shiki-dark:#C9D1D9}html pre.shiki code .skZ57, html code.shiki .skZ57{--shiki-default:#A5D6FF;--shiki-dark:#A5D6FF}html pre.shiki code .sEQcL, html code.shiki .sEQcL{--shiki-default:#79C0FF;--shiki-dark:#79C0FF}html .default .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}html.dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}",{"title":55,"searchDepth":77,"depth":77,"links":796},[797,798,799,800,801],{"id":429,"depth":77,"text":430},{"id":459,"depth":77,"text":460},{"id":646,"depth":77,"text":647},{"id":725,"depth":77,"text":726},{"id":755,"depth":77,"text":756},"2025-05-20","A primer on SPR technology - how it works, why it matters for drug discovery, and where the field is heading.",{},"/blog/what-is-spr",{"title":424,"description":803},"blog/what-is-spr",[809,810,811],"SPR","biophysics","drug-discovery","QJJrGtgTSblExfKtr1O8munhWc_6XHdON0iVqc-RHeA",1780474229364]