. * * window.aa needs to exist and be usable by ANY module's script, * however early it runs - main-nav's script, for one, runs near * the top of

91探花

, well before the real search-insights.js * so the download * begins as early as before. Repeat calls share the same downloads, a * failed load is retried on the next call, and the versions / SRI * hashes live only here. * * Algolia Insights is unaffected: window.aa above is still created in * on every page and queues events until search-insights loads. * * window.loadAlgoliaLibs({ priority: 'high' }) (Oct 2026): used by the * /search page, where the first results wait on these libraries. Chrome * gives async scripts low priority, behind images and fonts; this asks * for high instead (fetchpriority). Only the first call for a library * sets its priority - later calls share that download. */ (function (win, doc) { var LIBS = [ { ready: function () { return !!win['algoliasearch/lite']; }, src: 'https://cdn.jsdelivr.net/npm/algoliasearch@5.52.1/dist/lite/builds/browser.umd.js', integrity: 'sha256-I2oYUIvhx1g6l4lTP+yoERbzLIHKzw4AKaBRQPwIeDY=' }, { ready: function () { return !!win.instantsearch; }, src: 'https://cdn.jsdelivr.net/npm/instantsearch.js@4.98.0/dist/instantsearch.production.min.js', integrity: 'sha256-ngmqZk4WBxUw257aMYZayyNBd983INngagv0jI6Ecfs=' } ]; function loadOne(lib, options) { if (lib.ready()) return Promise.resolve(); // One download per library, shared by every caller; reset on // failure so the next call retries just the library that failed. if (lib.pending) return lib.pending; lib.pending = new Promise(function (resolve, reject) { var script = doc.createElement('script'); script.src = lib.src; script.integrity = lib.integrity; script.crossOrigin = 'anonymous'; script.async = true; if (options && options.priority === 'high') script.setAttribute('fetchpriority', 'high'); script.onload = function () { lib.ready() ? resolve() : reject(new Error('Loaded but not available: ' + lib.src)); }; script.onerror = function () { script.remove(); reject(new Error('Could not load ' + lib.src)); }; doc.head.appendChild(script); }); lib.pending.catch(function () { lib.pending = null; }); return lib.pending; } win.loadAlgoliaLibs = function (options) { return Promise.all(LIBS.map(function (lib) { return loadOne(lib, options); })); }; })(window, document); . */ window.hsConversationsSettings = window.hsConversationsSettings || {}; window.hsConversationsSettings.loadImmediately = false; (function (win) { var EVENTS = ['pointerdown', 'keydown', 'touchstart', 'scroll', 'mousemove', 'wheel']; var done = false; /* 19 Oct 2026 - chat widget layout shift (field CLS). Phones fail Core Web Vitals on CLS (p75 ~0.2 site-wide in CrUX for months). Biggest cause found: HubSpot's chat container is fixed to the bottom-right corner and changes size - 100x96 launcher to 282x253 when the welcome message pops up (~5 s after load), and to full screen when a visitor opens the chat. Its top-left corner moves, so Chrome scores it as a layout shift: 0.088 per page view at 360x640 (0.044 at 412x850), on every page. Taps happen inside the chat iframe, so the parent page never sees the input and the open/close shifts count too. Fix: whenever the container's size changes it is made transparent for 400 ms (Chrome doesn't score shifts of invisible elements), then shown again at its new size. Tested on live io1001 at 360x640 in a cookie-less frame: the 0.088 shift no longer appears. The chat itself is unchanged - it just appears 0.4 s later at each resize. Relies on HubSpot's container id; if that changes this does nothing (no error). */ function cloakChatResizes() { var ID = 'hubspot-messages-iframe-container'; function watch(c) { if (c.getAttribute('data-bb-cloak')) return; c.setAttribute('data-bb-cloak', '1'); var last = c.offsetWidth + 'x' + c.offsetHeight, timer = null; new MutationObserver(function () { var size = c.offsetWidth + 'x' + c.offsetHeight; if (size === last) return; last = size; c.style.setProperty('opacity', '0', 'important'); clearTimeout(timer); timer = setTimeout(function () { c.style.removeProperty('opacity'); }, 400); }).observe(c, { attributes: true, attributeFilter: ['style', 'class'], subtree: true, childList: true }); } var found = document.getElementById(ID); if (found) { watch(found); return; } if (!document.body || !('MutationObserver' in win)) return; var mo = new MutationObserver(function () { var c = document.getElementById(ID); if (c) { mo.disconnect(); watch(c); } }); mo.observe(document.body, { childList: true }); setTimeout(function () { mo.disconnect(); }, 30000); } function loadWidget() { var api = win.HubSpotConversations; if (api && api.widget && api.widget.status && api.widget.status().loaded) return; try { cloakChatResizes(); } catch (e) {} if (api && api.widget) api.widget.load(); } function onFirstInteraction() { if (done) return; done = true; EVENTS.forEach(function (type) { win.removeEventListener(type, onFirstInteraction, { passive: true }); }); var start = function () { if (win.HubSpotConversations) loadWidget(); else (win.hsConversationsOnReady = win.hsConversationsOnReady || []).push(loadWidget); }; if ('requestIdleCallback' in win) win.requestIdleCallback(start, { timeout: 1500 }); else setTimeout(start, 200); } EVENTS.forEach(function (type) { win.addEventListener(type, onFirstInteraction, { passive: true }); }); })(window);

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Custom iPSC-derived disease model cells

Custom iPSC-derived disease model cells

 

Your mutation of interest in our opti-ox powered human iPSC-derived cells

CDM Image 2-1

 

With this custom offering, you can now order your mutation of choice in 91探花鈥檚 opti-ox powered human-iPSC derived cells and receive consistent, defined, cryopreserved disease models that can be immediately incorporated into your experiments.

Every custom disease model comes with a genetically matched control, ioWild Type Cells, giving you confidence that even subtle variances in your data are attributable to your mutation of interest.

Remove the challenges associated with animal models, patient-derived cells and directed differentiation protocols from your workflows, and start collecting disease-relevant data you can trust in a human context. Each project begins as a conversation with our experts about your custom disease model needs.

Start the conversation today

Pair with a genetically matched control

Build your custom disease model into these wild type cell backgrounds. Use the genetically matched control in your experiments to make true comparisons in your data, and confidently link genotype to phenotype. 

ioWild Type Cells

ioGlutamatergic Neurons

cat no | io1001
ioGlutamatergic Neurons
ioWild Type Cells

ioSkeletal Myocytes

cat no | io1002
ioSkeletal Myocytes
ioWild Type Cells

ioMicroglia | Male

cat no | io1021
ioMicroglia | Male
ioWild Type Cells

ioGABAergic Neurons

cat no | io1003
ioGABAergic Neurons
ioWild Type Cells

ioMotor Neurons

cat no | io1027
ioMotor Neurons

Insights from our partners on Custom ioDisease Model Cells

"The access to better human cell-based in vitro disease models as generated within our partnership is transformational for the way we do drug discovery with our pharma and biotech clients. We can now provide discovery studies in human stem cell-based assays, where previously we would only do this in for example immortalised cell lines or more simple assay types.鈥�

 

Marijn Vleming


      Marijn Vlaming, PhD     
      Charles River Laboratories

 

 

Uncover subtle phenotypes

Identifying intrinsic, observable phenotypes in ioDisease Model Cells has the potential to streamline compound testing in drug discovery by reducing the need to induce disease-related phenotypes when modelling specific diseases. Discover the data generated by our industry partners below.

Data on our
disease models
Data on our
disease models

Huntington's disease

A Huntington's disease-relevant phenotype has been observed in ioDisease Model Cells developed for industry partners.
uncover subtle phenotypes in HD 2
In this example, Charles River Laboratories carried out functional characterisation of ioGlutamatergic Neurons HTT 50CAG/WT by using MaxWell鈥檚 MaxTwo high-density microelectrode array (MEA) platform. The data demonstrates a significant decrease in firing rate compared to wild-type isogenic control.
Now, Charles River Laboratories use this disease model in their . Their customers can access in vitro assays using a disease model that recapitulates the Huntington鈥檚 disease phenotype.
Read the application note

Amyotrophic lateral sclerosis (ALS)

ioDisease Model Cells built to study ALS show a significantly reduced neuronal firing phenotype compared to the isogenic control. 
uncover subtle phenotypes in ALS 4 copy

Using a microelectrode array (MEA)-based assay our ALS disease model (ioGlutamatergic Neurons TDP-43 M337V/M337V=) demonstrates a significant reduction in neuronal activity compared to the ALS disease model with a heterozygous mutation (ioGlutamatergic Neurons TDP-43 M337V/WT) and the wild-type isogenic control. Data courtesy of Charles River Laboratories. 

This indicates their potential as a relevant translational in vitro drug discovery model for ALS.

Charles River Laboratories Discovery team now offers these disease models alongside high-content imaging and gene expression analysis to support investigations into TDP-43 protein phosphorylation, mislocalisation, aggregation, and altered mRNA splicing, which are hallmarks of ALS and FTD. 

Dive into the data

Duchenne muscular dystrophy (DMD)

ASO-mediated Dystrophin restoration  demonstrated in ioSkeletal Myocytes DMD Exon 44 Deletion disease model cells
ioSkeletal Myocytes DMD Exon 44 Deletion disease model cells show dystrophin restoration by ASO-mediated exon skipping

The DMD disease model offers a valuable translational model to investigate methods for dystrophin restoration, such as ASO-mediated exon skipping.

In this example, ioSkeletal Myocytes (wild type control) and ioSkeletal Myocytes DMD Exon 44 Deletion (DMD Del Ex44) were treated by gymnosis with exon 45 skipping antisense oligonucleotide (ASO-1). The data shows a concentration-dependent increase in the amount of mRNA transcript (A) and dystrophin protein (B) in the DMD exon 44 deletion disease model cells, indicating that ASO-1 treatment has been successful in creating an in frame mRNA transcript for dystrophin that leads to protein expression. Data courtesy of Charles River Laboratories.

Dive into the data

Interested in generating your own ioDisease Model Cells?

Start a no-commitment project consultation with our experts today.

Start the conversation
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