The validation of Variants of Uncertain Significance (VUS) in LQTS using iPSC-CMs is a critical step towards gaining a better understanding of their pathogenicity. CRISPR/Cas9 gene editing is used to insert the variant into iPSCs derived from healthy individuals in order to determine whether it causes disease symptoms. Alternatively, gene editing can be used to correct the variant in patient-derived iPSCs to determine whether this reverses the disease phenotype. This approach allows investigation of the sufficiency and necessity of mutations for causing disease, while maintaining the same genetic background. For example, Garg et al. (2018) [47] found that patient-derived iPSC-CMs carrying the KCNH2-p.T983I variant exhibited significantly prolonged APD. Although 12.9% of the cells displayed arrhythmic activity such as EADs, the iPSC model demonstrated that even mild arrhythmias can be captured in LQTS studies. Treatment with a human ether-a-go-go-related gene (hERG) channel activator normalized APD, confirming the accuracy of the iPSC-CMs in reflecting patient responses. After introducing the same KCNH2-p.T983I variant into healthy control cells, the researchers observed an even more severe LQTS phenotype, further supporting the role of this mutation in LQTS. Conversely, correcting the variant in patient-derived cells restored normal phenotypes, including typical APD, and reduced arrhythmic activity. Interestingly, previous studies conducted using heterologous systems with gene editing may have led to incorrect conclusions regarding the pathogenicity of certain variants. For instance, the KCNQ1-p.A341V variant exhibited mild effects in vitro, but severe clinical symptoms [48], whereas the KCNQ1-p.Y111C variant showed severe loss of function in vitro, despite a low clinical risk of cardiac events [49]. These discrepancies can often be explained by differences in post-translational modifications or variations in the expression level of regulatory proteins in native human myocardium.

With the increasing use of next-generation sequencing (NGS), the number of identified gene variants linked to specific clinical phenotypes has grown exponentially, leading to an increase in uncharacterized VUS [50, 51]. The proportion of VUS varies across LQTS subtypes, ranging from 15–20% in LQT1, to over 30% in LQT3 due to the complexity of the SCN5A gene. For less common subtypes such as those involving the CACNA1C and CALM genes, VUS can account for up to 40–50% of the variants. By leveraging iPSC models and gene editing, researchers have been able to reclassify many VUS from uncertain to pathogenic or benign. For example, Chavali et al. (2019) [52] introduced the CACNA1C-p.N639T variant into a healthy iPSC line, resulting in significantly prolonged repolarization time and impaired calcium current inactivation, hence leading to its reclassification as likely pathogenic. Similarly, Yamamoto et al. (2017) [53] used patient-derived iPSC models to study the impact of the CALM2-p.N98S mutation on L-type calcium channel function, finding that it prolonged APD. Allele-specific silencing using CRISPR/Cas9 further demonstrated that removing the mutant allele could restore normal function, thereby providing key insights into the reclassification of VUS. iPSCs have also been used for functional validation of newly discovered LQTS genes. For example, Zhou et al. (2023) [54] combined genome sequencing and patient-specific sparagine-linked glycosylation 10B gene (ALG10B)-p.G6S iPSC-CMs. Compared to isogenic controls, these exhibited significantly prolonged APD and notable retention of hERG protein in the endoplasmic reticulum. Moreover, Lumacaftor rescue experiments systematically verified that ALG10B-p.G6S mutation leads to the LQTS phenotype by affecting hERG trafficking, suggesting that ALG10B may be a novel LQTS gene. These experiments demonstrate the importance of iPSC models used in combination with genome editing as a robust platform for understanding the functional impact of VUS and of new genes, thus improving the accuracy of LQTS diagnosis.

Modifier genes significantly influence the severity and clinical presentation of LQTS. While not directly causing LQTS, they modify how the disease manifests in individuals with pathogenic mutations. Modifier genes help to explain why patients with the same primary LQTS mutation can have different symptoms and outcomes. The identification of modifier genes typically involves three main approaches [55]: (1) Candidate gene approach. This targeted approach focuses on genes and genetic variants that are already known to be associated with QT interval and arrhythmias. For example, the NOS1AP gene is linked to QT interval prolongation and is considered to be a key modifier gene for LQTS [48]. (2) Genome-wide association studies (GWAS). This unbiased approach scans the entire genome for genetic variants linked to disease risk, thus helping to identify novel genetic markers or modifiers without relying on prior knowledge. (3) Family and founder population studies. The investigation of family members with the same pathogenic mutation but different clinical outcomes can reveal potential modifier genes.

iPSC-CMs provide a valuable platform for studying modifier genes. For example, Chai et al. (2018) [56] combined electrophysiological measurements of iPSC-CMs with whole-exome sequencing (WES) to identify two modifier genes associated with the LQT2 phenotype: KCNK17 and REM2. KCNK17 encodes a two-pore potassium channel that may counteract the repolarization defects caused by KCNH2 mutations by increasing the potassium current, thereby providing a protective effect. REM2 encodes a GTP-binding protein that regulates calcium channels. The REM2-p.G96A variant was found only in severe cases and was linked to increased I_Ca,L. Correcting this variant with CRISPR/Cas9 successfully restored the normal phenotype in patient cells. In addition, Lee et al. (2021) [49] identified two single nucleotide variants (SNVs) of the MTMR4 gene in asymptomatic LQTS iPSC-CMs that weakened Nedd4L activity and prevented excessive degradation of ion channels. After correcting these SNVs with CRISPR/Cas9, the ion channel degradation and electrophysiological characteristics of these cells were similar to those of symptomatic patients, thus confirming their protective role. It should be noted that each method for identifying modifier genes has its strengths and limitations, and they are often used in combination to enhance the accuracy of the findings.

The primary pathological mechanism of LQTS involves dysfunction of multiple ion channels, particularly potassium and sodium, and abnormal calcium handling which leads to abnormalities in cardiac action potentials [57, 58].

The KCNQ1 gene encodes for the alpha subunit of a potassium channel that generates the I_Ks during cardiac repolarization. When KCNQ1 is mutated (e.g., the KCNQ1-p.Y111C mutation [49]), the folding and transport functions of this channel are impaired and it is prevented from reaching the cell membrane. In patient-derived iPSC-CMs models, KCNQ1 mutations have been associated with reduced potassium ion flow, delayed repolarization, and QT interval prolongation. These abnormalities make cardiomyocytes more unstable during repolarization, increasing the risk of ventricular arrhythmias. Recent studies have highlighted the role of complex splicing events and protein degradation pathways in LQTS pathology. For example, Wuriyanghai et al. (2018) [59] reported that the KCNQ1-p.A344Aspl mutation led to aberrant splicing, potassium channel dysfunction, and increased EADs. These observations enhance our understanding of how splicing abnormalities can exacerbate LQTS. At the cellular level, the mutated KCNQ1 protein was either misfolded or failed to properly localize to the cardiomyocyte membrane, causing a significant reduction in I_Ks current density. This reduction results in prolonged action potential repolarization, which directly manifests as QT interval prolongation on an ECG.

The KCNH2 gene encodes a voltage-gated potassium channel that generates the I_Kr and mutations that cause incorrect folding or intracellular retention of the channel prevent its proper insertion into the cardiomyocyte membrane [60]. iPSC-CMs models have shown that hERG channel dysfunctions lead to reduced I_Kr currents, further impairing cardiac repolarization and prolonging the QT interval. Studies have also shown that KCNQ1 mutations may indirectly affect I_Kr through enhanced degradation. For example, some KCNQ1 mutations may increase the degradation of both KCNQ1 and hERG proteins through the upregulation of regulatory proteins such as Nedd4L, further weakening repolarization and worsening the LQTS phenotype. Additionally, research by Feng et al. (2021) [61] on the KCNH2 mutation hERG1-p.H70R in iPSC-CMs models suggests these mutations lead to decreased I_Kr currents and accelerated deactivation in cardiomyocytes, directly contributing to prolonged APD and consistent with the LQTS phenotype. The main molecular mechanism involves a reduction in the complex glycosylation forms of hERG1a protein, while the expression of hERG1b remains unaffected. This imbalance of subunits weakens I_Kr currents, with abnormal folding and trafficking defects in hERG1a leading to endoplasmic reticulum-associated degradation that reduces the expression of functional channels. The complexity of this molecular mechanism was further revealed by analysis of mRNA splicing and post-translational regulation, emphasizing the impact of subunit ratios on channel function.

SCN5A gene mutations delay inactivation of the NaV1.5 sodium channel and increase I_Na,L, causing persistent sodium influx. This prolongs APD and ventricular repolarization, contributing to inherited arrhythmias like LQT3 and Brugada syndrome. Kroncke et al. (2019) [62] found that iPSC-CMs with the p.R1193Q variant exhibited significant late sodium current, leading to prolonged action potentials and triggered activity in cardiomyocytes. These features could be reversed by the addition of phosphatidylinositol (3,4,5)-trisphosphate (PIP3), suggesting that the pathogenic mechanism of the p.R1193Q variant may involve PIP3-related regulatory pathways rather than mechanisms of direct channel inactivation. Additionally, Nieto-Marín et al. (2022) [63] used iPSC-CMs with Tbx5 gene mutations (p. D111Y and p. F206L) to examine changes in SCN5A gene expression and the resulting functional effects on the cardiac sodium channel NaV1.5. These authors found the Tbx5-p.D111Y variant increased the expression of CaMKII and its anchoring proteins, leading to an increase in the I_Na,L of Nav1.5 and thus prolonging the action potential duration.

Calcium homeostasis also plays an important role in the pathophysiology of LQTS. Mutations in CALM impair calcium binding, resulting in abnormal calcium transients, prolonged APD, and an increased risk of arrhythmias such as EADs and delayed afterdepolarizations (DADs). Ledford et al. (2020) [64] showed that LQTS-related mutations such as CALM-p.D96V and CALM-p.D130G significantly reduce small-conductance Ca²⁺-activated K⁺ channel currents through a dominant-negative effect. These CALM mutations may therefore worsen LQTS pathology by impairing Ca²⁺-dependent repolarization currents. The CALM-p. D96V mutation led to a significant reduction in apamin-sensitive currents in iPSC-CMs, whereas the inhibitory effect of CALM-p.F90L was weaker, indicating that different CALM mutations may affect small-conductance Ca²⁺-activated K⁺ channel function through distinct mechanisms. The CALM-p.D96V mutation, in particular, severely affected channel function by impairing Ca²⁺ binding.

In summary, understanding the pathophysiology of LQTS involves exploration of how various ion channel dysfunctions and abnormal calcium handling produce the LQTS clinical phenotype. The resulting knowledge framework provides a scientific basis to support targeted therapeutic strategies and personalized management of this life-threatening disorder.

Genotype-specific treatments have shown significant progress for congenital LQTS. In particular, beta-blockers can effectively reduce cardiac events by over 95% for LQT1, 75% for LQT2, and 60% for LQT3. Propranolol, atenolol, and nadolol have shown efficacy, whereas metoprolol is less effective. Chockalingam et al. (2012) [26] suggested that in addition to their membrane stabilizing effect, propranolol and nadolol block peak I_Na, and affect non-inactivating I_Na,L, thus further contributing to APD shortening. Sodium channel blockers may also be required for symptomatic LQT3 patients. Ma et al. (2013) [40] reported that mexiletine reduces I_Na,L, restores peak I_Na, and improves electrophysiological properties. However, limitations remain with the current treatments. Despite advances in genetics, around 25% of LQTS cases lack an identified causative gene, thereby complicating precise risk assessment and targeted treatment. Furthermore, even within the same family, individuals with the same mutation can exhibit different disease severities, making risk assessment and treatment planning challenging. In severe cases, such as newborns with certain SCN5A, CALM, or TRDN mutations, current therapies often fail, highlighting the need for more effective drugs. Additionally, the side-effects of beta-blockers can impair patient adherence, particularly in those with no or mild symptoms, increasing the risk of arrhythmic events. Although effective for some LQTS types, sodium channel blockers can have off-target effects that add to the complexity of treatment. Mutation-specific therapies, such as lumacaftor, are only effective for specific cases and are not broadly applicable across all LQTS types. These challenges highlight the need to better understand the genetic complexity of LQTS, improve risk assessment, and develop more effective therapies that target the diverse presentations of this condition.

iPSCs hold significant value in the study of gene-specific drug therapies because they provide a patient-specific cellular environment that enables the evaluation of drug efficacy, ion channel specificity, off-target effects, and potential side-effects. Comollo et al. (2022) [65] demonstrated that propranolol effectively inhibited late sodium current (I_Na,L) in LQT3 cardiomyocytes with LQT3-associated a three amino acid deletion (p.$\mathrm{\Delta }$KPQ, $\mathrm{\Delta }$=deletion, K=Lysine, P=Proline, Q=Glutamine) and p.E1784K mutations. The inhibitory effect was more pronounced for the latter mutation, and the action of propranolol on I_Na,L was stronger than its effect on the I_Kr channel. These observations indicate that propranolol may have minimal off-target effects and potentially fewer side-effects for the treatment of LQT3. Stutzman et al. (2023) [66] highlighted the importance of using iPSC-CMs for the functional characterization of new mutations such as SCN5A-p.F1760C, especially after the failure of conventional treatments. They found the p.F1760C mutation led to increased I_Na,L and a shift in channel inactivation, which traditional sodium channel blockers such as mexiletine could not manage effectively. However, phenytoin successfully reduced the prolonged APD in these cells, suggesting it may be an alternative therapy for LQT3 patients who are resistant to standard treatments. These examples demonstrate the utility of iPSC-CMs in understanding the impact of specific mutations and identifying targeted therapies, allowing for personalized treatment strategies in challenging cases. The success of phenytoin in restoring normal electrophysiological function in p.F1760C mutant cells suggests that repurposing anti-epileptic drugs could be an effective approach for treating variants that interfere with traditional drug binding. This case underscores the role of patient-specific cell models in bridging the gap between genetic diagnosis and effective therapy for channelopathies.

The comprehensive in vitro proarrhythmia assay (CiPA) is a new framework that integrates human-based computational models, in vitro assays, and iPSC-CMs. Due to their human origin and functional characteristics, iPSC-CMs are an effective platform for assessing drug-induced arrhythmias and other cardiac toxicities. Using multiparametric evaluations including electrophysiology, calcium signaling, cellular structure, and metabolic activity, in combination with high-content screening, iPSC-CMs are able to detect both arrhythmic and structural toxicities. When tested with drugs that are known to have arrhythmic risks, such as dofetilide and sotalol, iPSC-CMs accurately predicted the drugs’ potential to prolong APD and trigger arrhythmic activity, demonstrating their value in evaluating early toxicity to identify high-risk compounds. Therefore, iPSC-CMs serve as a powerful platform for testing drug efficacy against specific mutations and for uncovering potential anti-arrhythmic effects (Table 3, Ref. [40, 46, 67, 68, 69, 70, 71, 72, 73]). For example, Mehta et al. (2018) [72] used iPSC-CMs from LQT2 patients to evaluate the effect of Lumacaftor, a drug originally designed for cystic fibrosis. LQT2 is primarily caused by mutations in the KCNH2 gene, resulting in reduced I_Kr current due to hERG potassium channel misfolding and defective trafficking to the cell membrane. The authors showed that Lumacaftor successfully corrected these defects in iPSC-CMs to restore the normal function of hERG channels. Further validation of these findings were provided by Schwartz et al. (2019) [74], who conducted a clinical trial using a combination of Lumacaftor and Ivacaftor (LUM+IVA) in two LQT2 patients. Consistent with in vitroresults, both patients showed a significant reduction in QTc interval, albeit to a smaller degree compared to the cell studies. Although side-effects such as diarrhea were observed, the reduction in QTc interval during treatment, along with its subsequent rebound during drug washout, suggested a promising therapeutic effect. Another significant development was reported by Giannetti et al. (2023) [73], who explored the effects of serum/glucocorticoid-regulated kinase 1 (SGK1) inhibitors. They found that SGK1 inhibition consistently shortened APD in LQT2 models, but showed inconsistent outcomes in LQT1 models. This result suggests that SGK1 inhibitors have potential for genotype-specific therapeutic use, and reinforce the importance of genetic testing in guiding effective treatments. Overall, these advances illustrate how novel screening approaches and iPSC-CMs models are paving the way for more precise, personalized treatment of LQTS.

Biological therapies offer a promising new direction for treating LQTS by targeting the molecular root of the disorder. Suppression and replacement gene therapies have shown potential for addressing genetic mutations associated with LQTS. Dotzler et al. (2021) [75] reported that a novel suppression-replacement gene therapy (KCNQ1-SupRep) for LQT1 was an effective way to address mutant alleles while introducing functional ones. The suppression phase involved short hairpin RNA (shRNA) targeted at KCNQ1 and which reduced the expression of both mutant and wild-type alleles to mitigate harmful gene effects. The replacement phase used an immune-compatible KCNQ1 complementary DNA (cDNA) variant (shIMM) that was resistant to shRNA suppression and restored normal KCNQ1 protein function. This combined approach successfully shortened APD in iPSC-CMs and normalized the pathological features in a transgenic rabbit model of LQT1.

Optogenetic therapies have also emerged as potential tools for precise control of cardiac electrophysiology. Gruber et al. (2021) [76] explored the use of light-sensitive ion channels to regulate APD in iPSC-CMs from LQTS patients. Their approach used channelrhodopsin-2 (ChR2), a cation channel activated by blue light, to trigger the influx of sodium and calcium ions and thus cause cellular depolarization. By applying light at specific AP phases, these authors achieved bidirectional APD modulation: activation during phase 3 (repolarization) extended APD, whereas activation during phase 2 (early repolarization) shortened it. They also used anion channelrhodopsin-2 (ACR2), a chloride-selective channel, to shorten APD by promoting hyperpolarization. These optogenetic interventions showed promise in restoring normal APD and lowering arrhythmia risk, indicating that optogenetics may be a potential regulatory strategy for cardiac arrhythmias.

Additionally, monoclonal antibody therapy targeting the KCNQ1 potassium channel has shown potential for treating LQT3. Kis and Li (2024) [77] demonstrated the effectiveness of a monoclonal antibody (mAB-1) in normalizing the electrophysiological properties of iPSC-CMs. Using standard immunization techniques, they generated hybridoma cells from Balb/c mice spleen cells with high antibody titers, fused these with myeloma cells, and cultured them in HAT-supplemented RPMI 1640 medium. Six specific KCNQ1-targeting clones were selected and purified, with mAB-1 showing optimal function. In ATX-II-induced iPSC-CMs, mAB-1 effectively restored APD90 to baseline levels, suppressing EADs and arrhythmic activity. Together, these findings suggest that biological approaches have strong therapeutic potential in LQTS management.

iPSC-CMs often exhibit limited maturity, displaying embryonic-like electrophysiological characteristics. They lack the stability of adult cardiomyocytes, such as a stable action potential. Additionally, the absence of a T-tubule system restricts efficient intracellular calcium transfer, which impedes the analysis of calcium handling and triggered activity [78]. The resting membrane potential in iPSC-CMs is also less stable due to insufficient I_K1 expression and an elevated “funny current” (If), affecting their ability to accurately replicate adult cardiomyocyte electrophysiology [79]. Furthermore, discrepancies in ion channel kinetics, such as those observed with I_Ks, result in variable electrophysiological responses compared to mature heart cells. Several strategies have been explored to improve the maturity of iPSC-CMs. Gene transduction and current injection [80, 81], specifically through Kir2.1 transduction or simulated I_K1 injection, enhance I_K1 density, thereby promoting a more stable resting membrane potential and physiologically accurate AP morphology. Hormonal treatment, including thyroid hormone exposure, can induce features more similar to adult cardiomyocytes. Additionally, the culturing of cells on nano-structured or biomimetic substrates also supports structural and functional maturation by providing a more physiologically relevant environment. The optimization of differentiation conditions facilitates the generation of cells with predominantly atrial or ventricular characteristics, further increasing their specificity and maturity. Lastly, three-dimensional (3D) tissue culture [82, 83, 84] methods, such as microspheres or myocardial tissue strips, fosters stable beating and electrophysiological characteristics that closely resemble actual heart tissue. Collectively, these approaches enhance iPSC-CM maturity, improving their utility for electrophysiological and pharmacological screening studies.

The heterogeneity of iPSC-CMs primarily arises from molecular variations during differentiation that are shaped by specific signaling pathways, growth factors, and cytokine responses. Differentiating cardiomyocyte subtypes, such as ventricular, atrial, and nodal cells, rely on precisely regulated signaling pathways such as the Wnt and BMP pathways. Even minor differences in the timing and strength of these signals can produce mixed populations with diverse phenotypes, thereby reducing iPSC-CMs homogeneity. For example, Wnt activates progenitor formation, whereas its inhibition promotes differentiation. BMP2 contributes to myocardial differentiation, while Notch and fibroblast growth factor (FGF) regulate cell fate and proliferation, ensuring coordinated cardiac development. Additionally, transcription factors such as NK2 homeobox 5 (NKX2.5), T-box transcription factor 5 (TBX5), and short stature homeobox 2 (SHOX2) play crucial roles in cell fate during differentiation. Variation in the expression of these factors leads to mixed ventricular and atrial phenotypes within the same culture, impacting the consistency of the generated iPSC-CMs. Culture conditions, whether two-dimensional (2D) or 3D, also affect cell-cell interactions and phenotypic stability.

To address these challenges, several strategies have been developed to increase the homogeneity of iPSC-CMs: (1) Optimization of the differentiation protocols through modulation of the Wnt and BMP pathways can lead to more specific iPSC-CM subtypes [85]. Small molecule inhibitors can be used to refine the timing and strength of pathway activation, resulting in more uniform cell populations. (2) Advanced co-culture systems with supportive cardiac cells, such as endothelial cells and fibroblasts, help to create a more physiological environment. This promotes stable differentiation and phenotypic consistency by mimicking natural cardiac signals. (3) Gene editing tools such as CRISPR/Cas9 can further improve iPSC-CM stability by reducing spontaneous gene expression changes, facilitating the development of more uniform cell lines suitable for disease modeling. (4) Defined culture media containing specific fatty acids and supplements that mimic the metabolic profile of the human heart contribute to more consistent maturation across iPSC-CMs populations. (5) Expanding iPSC-CMs in 3D bioreactors provides a controlled environment for dynamic cell growth and reduces heterogeneity compared to static cultures. Such bioreactor systems allow real-time adjustments of the growth conditions and support reproducible, large-scale differentiation. Standardization and scalability is essential to ensure that iPSC-CMs can be produced at the scale required for widespread clinical and research use. Lee et al. (2020) [86] recently developed a primordial 3D heart-like structure using mouse embryonic stem cells (ESCs) and FGF signaling. This structure included defined atrium, ventricle, pacemaker cells, smooth muscle cells (SMCs), and endothelial cells (ECs). Similarly, Hofbauer et al. (2021) [87] generated self-organizing “cardioids” using human iPSCs. These contained cells from the myocardium, epicardium, and endocardium, successfully mimicking the early development of heart chambers. However, integrating multicellular coupling models to study intercellular coupling properties and synchrony, and exploring the propagation of electrical signals and repolarization of iPSC-CMs in 3D tissue cultures or engineered heart tissues, remains a significant challenge.

Computational models are widely used to study mechanisms of cardiac automaticity and arrhythmias [88]. They offer precise control over parameters so that the compensatory effects seen in genetic animal models can be overcome, while also allowing simultaneous and detailed analysis of multiple components, including ion currents, membrane potentials, and intracellular concentrations. Consequently, these models have significant value in the CiPA initiative, which aims to predict the proarrhythmic risk of new drugs. However, the models are becoming increasingly complex as our understanding of cardiac electrophysiology deepens, since they integrate molecular ion channel dynamics, localized calcium handling changes, and post-translational regulation through signaling cascades [89].

Standard iPSC-CMs AP models typically encompass detailed dynamics of sodium (Na⁺), calcium (Ca²⁺), and potassium (K⁺) channels, which are used to study voltage changes under normal and pathological conditions. Many models are based on the AP models of mature cardiomyocytes, with parameter adjustments to accommodate the unique characteristics of iPSC-CMs. For example, the Paci model aims to replicate the dynamic characteristics of AP and calcium handling. This makes it suitable for simulating the effects of drugs on ion channels, and in particular for evaluating the proarrhythmic risk of new drugs. Additionally, this model can be adjusted to simulate different cardiomyocyte subtypes. However, iPSC-CMs often retain embryonic-like phenotypes, and hence the Paci model may not accurately reflect the structure and function of mature cardiomyocytes. Another model developed by Koivumäki et al. (2018) [90] focuses on the impact of the immature characteristics of iPSC-CMs on cellular function. It provides a detailed description of calcium handling and action potential properties, and offers a virtual platform for simulating disease mechanisms. This model is particularly suitable for studying differences in electrophysiological characteristics between iPSC-CMs and mature cardiomyocytes. It effectively simulates the impact of the lack of mature T-tubule structures in iPSC-CMs, allowing for an in-depth analysis of calcium handling abnormalities and their potential contribution to arrhythmias. It is useful for disease modeling and drug screening, helping to predict the specific effects of drugs on immature cardiomyocytes.