How do people make their scientifique drawing really?
A complete list presenting free and freemium options
The Complete Guide to Scientific Illustration Software for Researchers
Scientific illustration is such an important topic when it comes to scientific communication. A good illustration can transform your poster or paper from mediocre to exceptional—or unfortunately, the complete opposite if done poorly.
I’m sure you’ve stumbled upon a figure that made you stop and think, “What tool did they use to make this? This figure is wow.” The structure, the colors, the forms, the legend—everything seems to be in exactly the right place. These moments of visual clarity are what separate good science from great science communication.
In this article, I’ll focus on drawing and design tools that involve manual creation. I’ll cover the topic of scientific illustrations made by code (like matplotlib, ggplot2, and others) in a future article.
Whether you’re a master’s student preparing your first conference poster or a seasoned researcher submitting to high-impact journals, choosing the right illustration tool can dramatically affect your productivity and the quality of your visual communication. I’ll walk you through the most widely used software options—some free, others paid or freemium—and help you understand which tool fits your needs, skill level, and budget.
For each software, I’ll cover:
Key characteristics and what makes it unique
Difficulty level and learning curve
Time investment to become proficient
Potential and best use cases
Limitations you should be aware of
The Free Options: Powerful Tools Without Breaking the Bank
Inkscape: My Personal Favorite
What it is: Inkscape is a professional-grade, open-source vector graphics editor that rivals paid alternatives like Adobe Illustrator. It’s been the backbone of countless scientific publications and is particularly beloved in the academic community.
Key Characteristics:
Native SVG format with export to PDF, PNG, EPS
Comprehensive path editing and node manipulation
Advanced features: gradients, patterns, clones, and markers
Extensible with Python scripts and extensions
Cross-platform (Windows, Mac, Linux)
Active community and extensive documentation
Difficulty Level: Intermediate. The interface can feel overwhelming at first, but it follows standard vector editing conventions.
Time to Learn: 2-4 weeks for basic competency, 2-3 months to master advanced features. The learning curve is worth it.
Potential: Unlimited. Publication-quality figures, complex molecular diagrams, annotated microscopy images, flowcharts, and complete poster designs. Professional outputs comparable to Adobe Illustrator.
Limitations:
Steeper learning curve than simpler tools
Interface feels dated compared to modern apps
Performance can lag with extremely complex files
Text handling is less refined than in commercial software
Collaboration features are minimal
Best for: Researchers who want complete control and professional results without ongoing costs.
Draw.io (now Diagrams.net)
What it is: A free, browser-based diagramming tool specifically designed for flowcharts, network diagrams, and schematic representations. No installation required.
Key Characteristics:
Web-based with optional desktop app
Extensive library of pre-made shapes and icons
Integrates with Google Drive, OneDrive, GitHub
Real-time collaboration capabilities
Template library for common diagram types
Free with no watermarks or limitations
Difficulty Level: Beginner-friendly. Intuitive drag-and-drop interface.
Time to Learn: 1-3 days for basic proficiency. Most researchers are productive within hours.
Potential: Excellent for experimental workflows, methodological flowcharts, system architectures, and conceptual diagrams. Perfect for methods sections and supplementary materials.
Limitations:
Not designed for artistic illustration or detailed molecular structures
Limited fine-tuning of visual aesthetics
Export quality can be inconsistent at very high resolutions
Less control over typography and design elements
Not suitable for complex figure assembly
Best for: Quick methodological diagrams, process flows, and conceptual frameworks.
Google Slides
What it is: Yes, Google’s presentation software! Often overlooked but surprisingly powerful for scientific figure creation, especially for those already familiar with the interface.
Key Characteristics:
Cloud-based with automatic saving
Real-time collaboration with co-authors
Simple, familiar interface
Basic shape tools and alignment features
Easy integration with Google Drive ecosystem
Export to PDF, PNG, SVG, and PowerPoint
Difficulty Level: Beginner. If you’ve made a presentation, you can make a figure.
Time to Learn: Immediate for basic use, 1-2 weeks to master figure-making techniques.
Potential: Surprisingly versatile for simple schematics, concept diagrams, and multi-panel figure assembly. Many published figures were made in Google Slides.
Limitations:
Very limited illustration capabilities
Crude path editing and object manipulation
Poor text rendering in exports
Not vector-native (though exports can be vector)
Limited color management and precision
Professional designers will spot it immediately
Best for: Rapid prototyping, collaborative figure drafting, and researchers with minimal design experience who need something quick.
Figma
What it is: A modern, collaborative interface design tool that has revolutionized how design teams work together. Increasingly popular in scientific illustration for its real-time collaboration features.
Key Characteristics:
Browser-based and desktop app available
Real-time multiplayer editing
Professional-grade vector tools
Component and style systems for consistency
Version history and branching
Free for individual use with limitations
Difficulty Level: Intermediate. Modern interface with a learning curve, but extensive tutorials available.
Time to Learn: 1-2 weeks for basics, 1-2 months for advanced features. The interface is more intuitive than traditional tools.
Potential: Exceptional for creating design systems for consistent figure styling across papers. Excellent for collaborative figure development with co-authors. Publication-quality outputs.
Limitations:
Free version limits number of files and version history
Requires internet connection for full functionality
Less extensive scientific symbol libraries than specialized tools
Some advanced typography features missing
Not specifically designed for scientific content
Best for: Labs creating consistent visual identities, collaborative projects, and researchers comfortable with modern design tools.
Canva
What it is: A user-friendly, template-driven design platform that has exploded in popularity. While aimed at general graphic design, it has surprising utility for scientific figures.
Key Characteristics:
Huge template library (some science-specific)
Drag-and-drop simplicity
Stock photo and element libraries
Basic animation capabilities
Free tier with limitations (paid elements, export quality)
Mobile app available
Difficulty Level: Very beginner-friendly. Easiest tool on this list.
Time to Learn: Hours. You can create your first usable figure immediately.
Potential: Great for conference posters, graphical abstracts, social media graphics, and presentations. Quick turnaround for visually appealing but simple figures.
Limitations:
Limited precision and control
Many premium elements require paid subscription
Export quality limitations on free tier
Not suitable for detailed technical illustrations
Generic aesthetic that lacks professional polish
Watermarks on free elements
Heavy reliance on templates can lead to unoriginal work
Best for: Researchers needing attractive posters or graphical abstracts quickly, especially those with no design background.
The Paid Options: Professional Power and Specialized Features
PowerPoint (Microsoft 365)
What it is: Microsoft’s presentation software that doubles as a surprisingly capable vector graphics editor for scientific figures. The tool many researchers already own.
Key Characteristics:
Native alignment and distribution tools
Advanced object grouping and ordering
Shape merge and fragment operations
Excellent text handling
Integration with other Office apps
Available through most institutional licenses
One-time purchase or subscription ($6.99-$9.99/month personal)
Difficulty Level: Beginner to Intermediate. Most researchers already know the basics.
Time to Learn: Immediate for basic use, 2-3 weeks to master figure-specific techniques.
Potential: Highly capable for scientific schematics, multi-panel figures, annotated images, and diagram creation. Used in countless published papers. EMF vector export for publication quality.
Limitations:
Not a dedicated illustration tool
Path editing is clunky compared to true vector editors
Color management is basic
Large files with many high-res images become sluggish
Cross-platform compatibility issues (Mac vs. Windows)
Output quality depends heavily on export settings knowledge
Best for: Researchers already paying for Office 365 who want a familiar interface with reasonable capabilities.
Adobe Illustrator
What it is: The industry-standard professional vector graphics software used by designers and illustrators worldwide. The gold standard against which all other tools are measured.
Key Characteristics:
Unmatched precision and control
Comprehensive path editing and bezier tools
Advanced typography and color management
Integration with Photoshop and other Adobe apps
Extensive plugin ecosystem
Professional color profiles (CMYK, spot colors)
Subscription required ($22.99/month single app, $59.99/month Creative Cloud)
Difficulty Level: Advanced. Significant learning curve but extremely powerful.
Time to Learn: 1-2 months for competency, 6-12 months to master. Investment pays off for career-long use.
Potential: Unlimited. Anything visual you can imagine, from molecular diagrams to complete journal covers. Publication-ready outputs with perfect quality control. Industry standard for professional scientific illustration.
Limitations:
Expensive ongoing subscription
Overwhelming interface for beginners
Overkill for simple diagrams
Requires significant time investment
Frequent updates can change workflows
Not specifically designed for scientific content (no built-in molecular tools)
Best for: Serious researchers investing in long-term illustration capabilities, those producing high-volume publications, and anyone needing absolute control and professional quality.
Vectr
What it is: A relatively new, simplified vector graphics editor designed for ease of use. Positioned as a lightweight alternative to Illustrator.
Key Characteristics:
Free for basic use
Web-based and desktop versions
Real-time collaboration
Simple, clean interface
Basic vector editing tools
No watermarks
Difficulty Level: Beginner. Very accessible interface.
Time to Learn: 1-2 days for basic proficiency.
Potential: Good for simple scientific diagrams, basic schematics, and learning vector concepts before advancing to more complex tools.
Limitations:
Very limited compared to professional tools
Missing advanced features essential for complex work
Small user community and fewer tutorials
Limited export options
Not widely adopted in scientific community
Development seems to have slowed
Best for: Absolute beginners wanting to learn vector graphics concepts without investment or complexity.
Affinity Designer
What it is: A professional vector graphics editor positioned as a one-time purchase alternative to Adobe Illustrator. Increasingly popular among academics tired of subscription models.
Key Characteristics:
One-time purchase ($74.99, often on sale for $39.99)
Professional-grade features rivaling Illustrator
Both vector and raster editing in one app
Advanced typography and color management
iPad version available (separate purchase)
No subscription required
Regular feature updates included
Difficulty Level: Intermediate to Advanced. Similar complexity to Illustrator.
Time to Learn: 3-6 weeks for competency, 2-4 months for advanced use.
Potential: Publication-quality outputs for all types of scientific illustration. Nearly matches Illustrator’s capabilities at a fraction of the cost. Excellent for researchers who need professional tools but reject subscription models.
Limitations:
One-time cost still significant for students
Smaller community than Adobe products
Fewer third-party plugins and extensions
Some specialized scientific tools not available
Learning resources less abundant than for Adobe
No equivalent to BioRender’s biological libraries
Best for: Researchers wanting professional capabilities with one-time payment, especially those committed to avoiding subscription models.
BioRender
What it is: The game-changer for biological research. A specialized tool built specifically for creating biological and medical illustrations with extensive libraries of pre-made, scientifically accurate elements.
Key Characteristics:
Massive library of biological icons (cells, proteins, organs, techniques)
Pre-made templates for common figure types
Scientifically accurate representations
Simple drag-and-drop interface
Citation features and attribution
Export with watermark (free) or clean (paid)
Subscription: $0 (basic), $179-299/year (individual), $799+/year (lab)
Difficulty Level: Beginner. Designed for scientists, not designers.
Time to Learn: 1-3 days to create first publication-quality figure.
Potential: Exceptional for cell biology, molecular biology, immunology, neuroscience, and medical research figures. Dramatically reduces figure creation time. Standardized, professional aesthetic. Widely accepted by journals and peers.
Limitations:
Requires subscription for watermark-free exports
Limited to biological/medical sciences
Less flexibility than general illustration tools
Can’t create highly custom or novel representations
Style is recognizable (figures look like “BioRender figures”)
Expensive for individuals without lab budgets
Free version has significant export restrictions
Best for: Biological and medical researchers who need consistent, professional figures quickly and want scientifically accurate pre-made components.
Comparison Table: Finding Your Perfect Match
Software Cost Difficulty Learning Time Best For Vector Native Collaboration Export Quality Inkscape Free Intermediate 2-4 weeks Complete control, professional results ✓ Limited Excellent Draw.io Free Beginner 1-3 days Flowcharts, diagrams ✓ ✓ Good Google Slides Free Beginner Immediate Quick schematics, collaboration Partial ✓ Fair Figma Free/Paid Intermediate 1-2 weeks Design systems, collaboration ✓ ✓ Excellent Canva Free/Paid Beginner Hours Posters, graphical abstracts Partial ✓ Good PowerPoint $7-10/mo Beginner-Int Immediate Familiar interface, diagrams ✓ ✓ Good-Excellent Illustrator $23-60/mo Advanced 1-2 months Professional illustration ✓ Limited Excellent Vectr Free Beginner 1-2 days Learning vectors ✓ ✓ Fair Affinity $75 once Intermediate-Adv 3-6 weeks Professional without subscription ✓ Limited Excellent BioRender $179-799/yr Beginner 1-3 days Biological/medical figures ✓ ✓ Excellent
Finding Your Perfect Match: What You Should Use at Each Stage
Look, I know choosing software can feel overwhelming. You’re probably thinking “I just need to make a decent figure for my thesis, why are there so many options?” So let me break this down based on where you are in your academic journey, because honestly, your needs change dramatically as you progress.
If You’re in Your Bachelor’s or Master’s Program
Here’s the thing—you’re juggling classes, labs, maybe a part-time job, and suddenly your supervisor wants a figure for your thesis that looks professional. You don’t have time to become a design expert, and you definitely don’t have money to throw at expensive software.
Start with Google Slides or Canva. I know, I know, it sounds too simple. But trust me, you can create perfectly acceptable figures for coursework and even your thesis defense. These tools let you focus on your science rather than wrestling with complicated software. Plus, when you’re collaborating with classmates on group projects, everyone already knows how to use them.
That said, if you’ve got a summer break coming up and you know you’re heading toward a research career, spend some time learning Draw.io for flowcharts and methodology diagrams. It’s incredibly intuitive and you’ll use these skills constantly in your PhD. And honestly? If you’ve got the motivation, start playing with Inkscape. Watch some YouTube tutorials while you eat lunch. The investment will pay off big time when thesis time rolls around.
The beauty of this stage is everything can be completely free. Inkscape plus Draw.io plus Google Slides covers pretty much everything you need. Save your money for conference travel instead.
When You’re Deep in Your PhD
Okay, this is where things get real. You’re not making figures for a grade anymore—you’re making figures that reviewers at Nature Communications are going to scrutinize. This is when you need to level up, and I’m going to be straight with you: learn Inkscape properly.
I recommend dedicating your first couple of months to really mastering it. I mean really learning it, not just fumbling through tutorials. Take a weekend, download some practice files, follow a comprehensive course. It feels like a lot upfront, but you’re going to create dozens of figures over the next few years. Every hour you invest now saves you five hours later when you’re frantically revising figures at 2 AM because Reviewer 2 wants everything in a different color scheme.
Here’s what nobody tells you—create a personal style guide early. Pick your fonts, your color palette, your line weights, and stick to them across all your figures. When you’re assembling your thesis three years from now, you’ll thank yourself because everything already looks cohesive. Nothing screams “I made these figures over five years with no plan” like wildly different styles in every chapter.
If you’re in biological sciences and your lab has a BioRender subscription, absolutely use it. It’s honestly a game-changer for cell biology figures. But don’t rely on it exclusively—you still need to know a general-purpose tool like Inkscape because BioRender won’t help you when you need to annotate microscopy images or create custom schematics.
Budget option? Inkscape all the way, combined with Draw.io for quick flowcharts. Both are free, both are powerful, and both produce publication-quality outputs. If your PI asks why your figures look so good, you can just smile knowingly.
Now, if you’ve got some fellowship money burning a hole in your pocket or your institution provides software licenses, Affinity Designer for seventy-five bucks is absolutely worth it. It’s basically Illustrator but you only pay once. Some people prefer it to Inkscape because the interface feels more modern. BioRender individual plans run about $180-300 per year if you’re in wet lab biology and you’re pumping out multiple papers.
Once You’re a Postdoc
Let’s be real—your postdoc is your audition for the rest of your career. Your first-author papers during this time determine whether you get that faculty position or industry job you want. Your figures need to be not just good, but outstanding. This is when efficiency becomes crucial because you’re supposed to be productive while also applying for jobs, writing grants, and possibly mentoring students.
If you’ve been using Inkscape through your PhD, honestly, keep using it. You’re already fast with it, you know its quirks, and it produces professional results. Don’t underestimate the value of working with a tool you’ve mastered. I’ve seen people waste months trying to learn Illustrator when they were already perfectly competent with Inkscape.
That said, if your institution offers Adobe Creative Cloud licenses (many do for postdocs), go ahead and learn Illustrator. The main advantage isn’t that it’s necessarily better than Inkscape—it’s that every professional scientific illustrator uses it, so if you ever need to collaborate with them or hire them later, you’re speaking the same language. Plus, having Photoshop integrated is genuinely useful when you’re working with microscopy images.
Budget option? Stick with Inkscape. Seriously. I know multiple successful PIs who still use it for all their figures. It’s completely viable at every career level. Pair it with Draw.io and you’re set.
If you want to invest in your toolset, grab Affinity Designer for that one-time seventy-five dollar payment. You get professional-grade capabilities without the subscription. For biological sciences people, a BioRender professional plan at about $300 per year might actually save you enough time to write another paper, which more than pays for itself.
The bigger investment at this stage should honestly be taking a weekend workshop on scientific illustration principles if one’s available. Understanding design theory will improve your figures more than any software upgrade will.
If You’re Running Your Own Lab
Alright, Professor, your situation is different. You’re probably not making most of your figures anymore—you’re editing your students’ figures at midnight before a submission deadline. You need tools that let you work fast and make global changes quickly. You also need to establish lab standards so your papers have a consistent visual identity.
Adobe Illustrator is probably your best bet at this stage if you can swing the budget. The main reason isn’t even the software itself—it’s that when you hire that talented undergraduate who learned Illustrator in their design minor, or when you collaborate with that structural biologist whose lab uses Illustrator, everything just works. The ecosystem matters more than the features at this level.
That said, I know PIs running successful labs entirely on Inkscape. If you establish it as your lab standard, train everyone who joins, and maintain a shared library of templates and elements, it works beautifully. You can have one lab computer with Inkscape and a tablet for anyone who needs to create figures. Total cost: zero dollars.
Consider getting a lab BioRender subscription if you’re in the life sciences. It’s around $800 per year for a lab license, which sounds like a lot until you realize it saves your five PhD students about two hours each per figure. That’s dozens of hours per year, which translates to actual research time. Talk to your department—sometimes they have educational licenses that are cheaper.
Here’s a pro tip: invest in establishing really solid lab templates and style guides. Use Figma’s free team plan to create a shared library where everyone can access your lab’s standard color palettes, figure panel sizes, and font choices. This upfront investment saves ridiculous amounts of time when you’re trying to assemble multi-figure papers with contributions from different lab members.
And honestly? For your really high-impact papers—the ones going to Cell or Nature—consider hiring a professional scientific illustrator for a few hours. They typically charge $100-200 per hour, and they can take your draft figures and make them absolutely stunning. That graphical abstract that makes your paper pop on Twitter? Worth every penny.
Beyond the Software: What Actually Makes Figures Great
Here’s something that took me way too long to learn—the software is honestly the least important part of making great figures. I’ve seen gorgeous figures made in PowerPoint and terrible figures made in Illustrator. What really matters is understanding some basic principles.
Think about visual hierarchy for a minute. When someone looks at your figure, their eyes land somewhere first, then move to a second spot, then a third. You need to control that journey. Use size, color, and position deliberately to guide them through your data in exactly the sequence that tells your story. Your main result should jump out. Your controls should be visible but not competing for attention. Your statistical annotations should be clear but not overwhelming.
Let’s talk about color because this is where I see people mess up constantly. About 8% of men and 0.5% of women have some form of color vision deficiency. That red-green comparison you’re so proud of? A big chunk of your audience literally cannot see the difference. Use ColorBrewer palettes—they’re designed to be colorblind-friendly. Run your figures through a colorblind simulator before submitting. It takes thirty seconds and might save your paper from being misunderstood.
File formats matter more than you think. Vector formats like SVG, PDF, and EPS are essential for anything with lines or text—diagrams, schematics, graphs. They scale infinitely without losing quality. Raster formats like TIFF and PNG are for photographs and microscopy images. Use 300 DPI minimum for print, 600 DPI if you’ve got high-resolution microscopy. And please, never use JPEG for scientific figures. The compression creates artifacts that make your data look sloppy.
Different journals have different requirements, and this catches people off guard during submission. Nature journals want your multi-panel figures assembled with subfigure labels included. Cell Press wants individual panels submitted separately and they add the labels themselves. Read the author guidelines before you create your final versions, not after. Trust me on this—reformatting figures at the submission stage is miserable.
Version control will save your sanity. Save your figures as figure1_v1.svg, figure1_v2.svg, and so on. Never overwrite previous versions. I cannot count the number of times Reviewer 2 has asked for something I had in version 4 but changed in version 8. If you’ve kept your versions, it’s a five-minute fix. If you haven’t, you’re recreating everything from scratch.
Show your drafts to people early and often. Your labmates will catch things you miss. Your advisor will have opinions before the submission deadline rather than during frantic last-minute revisions. If you’re on academic Twitter or Mastodon, the #sciart and #scicomm communities are incredibly generous with feedback. I’ve gotten better figure advice from random internet scientists than from some of my colleagues.
Create templates for yourself. Standard panel sizes, consistent fonts, your preferred label style. When all your figures follow the same basic template, your papers look professional and cohesive. Nobody should be able to tell that you made Figure 1 three years before Figure 5.
So What Should You Actually Do?
Look, there’s no universal “best” tool. Anyone who tells you otherwise is probably selling something. The right answer depends entirely on your specific situation—your field, your career stage, your budget, your existing skills.
If you’re just starting out, begin with whatever feels least intimidating. Make something. Anything. Get over the initial hurdle of creating your first figure. Google Slides is fine for this. Canva is fine for this. The goal is just to start.
If you’re serious about a research career, invest the time to learn Inkscape properly or save up for Affinity Designer. This is a skill you’ll use for decades. The learning curve is real but the payoff is enormous. You’ll never regret becoming proficient with a professional tool.
If you’re in biological sciences, BioRender is legitimately transformative. I was skeptical at first—it seemed expensive and limiting—but watching my biologist friends cut their figure-making time in half while producing more consistent, clearer figures convinced me. If you’ve got the budget or your lab has a subscription, use it.
If you’ve got funding and you’re producing high volumes of publications, Adobe Illustrator remains the gold standard. The ecosystem, the resources, the fact that everyone knows it—these things matter when you’re at that level.
But here’s the most important thing: the tool matters way less than your understanding of visual communication. A skilled person can make publication-quality figures in PowerPoint. A beginner will make mediocre figures even with the fanciest software. Focus on learning the principles, practice deliberately, and your figures will improve regardless of which tool you pick.
Start somewhere. Make something imperfect. Iterate. Learn. Your figures will get better with every single one you create.
What tool are you using now? What’s working for you and what’s frustrating you? Drop a comment and let’s talk about it. And if you want to see tutorials on specific techniques or tools, let me know—I’m planning follow-up articles and I want to cover what’s actually useful to you.